I asked chatbots to find unusual ways to use the tools they have access to. I discovered ffmpeg can visualize audio via filters, then compiled over 100 creative workflows for tools like ImageMagick, Pandoc, and Graphviz.

I asked the popular chatbots for creative ways to use tools they have access to. Here are the responses. Expand to read their responses: Claude's ideas Original Claude conversation 🤯 Hidden Capabilities: Creative Tool Combinations Nobody Thinks Of A compendium of mind-blowing workflows using standard tools in unexpected ways Strategy Framework | Strategy | Description | Example | |----------|-------------|---------| | S1 | Single tool, hidden feature | FFmpeg generative fractals | | S2 | Single tool, chained workflows | Multiple FFmpeg filters → collage | | S3 | Cross-domain tool fusion | Audio → Visual → Document | | S4 | Data as unexpected medium | Code → Art, Logs → Music | | S5 | Reverse/inverse operations | Video → Audio, Image → Code | | S6 | Generative/procedural content | Algorithmic art, data-driven generation | | S7 | Meta-tool operations | Tools operating on tool outputs | 🎬 FFMPEG SORCERY 1. Fractal Video Generator (S1) FFmpeg can generate Mandelbrot fractals as video - no input needed! Mind-blow: Create infinite zoom videos, educational math content, or mesmerizing backgrounds without any source material. 2. Game of Life Simulator (S1) FFmpeg has Conway's Game of Life built in! Mind-blow: Generate cellular automata art, screensavers, or visualize emergent complexity. 3. Sierpinski Triangle Animation (S1) Generate fractal geometry videos: 4. Audio-Reactive Kaleidoscope (S2) Chain audio visualization with kaleidoscopic transformations: 5. Audio DNA Fingerprint (S1) Generate a unique visual fingerprint of any audio file: Mind-blow: Visual music identification, audio forensics, plagiarism detection visualization. 6. 3D Audio Sculpture (S1) The a3dscope filter creates rotating 3D visualizations from audio: 7. Phase Correlation Visualizer (S1) Visualize stereo phase relationships - reveals hidden mastering secrets: 8. Audio Waveform Art with Custom Coloring (S2) Create Instagram-worthy waveform art: 9. Continuous Wavelet Transform Visualization (S1) showcwt - Cutting-edge time-frequency analysis visualization: 10. Multi-Band Audio Spectrum (S2) Split audio into frequency bands and visualize each separately: 11. Video Datamoshing Effect (S1) Corrupt I-frames for glitch art: 12. Temporal Slit-Scan Photography (S1) Create time-slice effects like the "bullet time" in The Matrix: 13. Audio-Driven Text Animation (S2) Make text pulse with audio volume: 14. Video to ASCII Art Video (S2) Real-time ASCII art conversion: 15. Chromatic Aberration Effect (S1) Create that trendy RGB split effect: 🖼 IMAGEMAGICK WIZARDRY 16. Stereogram Generator (S1) Create Magic Eye images from depth maps: 17. Image to Sound to Image (S3) Convert image pixels to audio frequencies, then back: Mind-blow: Images have a "sound"! Compare similar images by their audio signatures. 18. Droste Effect Generator (S1) Create recursive self-containing images: 19. Morphological Image Processing for Art (S1) Use erosion/dilation for artistic effects: 20. Photomosaic Generator (S2) Create photo mosaics from a library of images: 21. Image Frequency Domain Art (S1) Visualize the FFT of images: 22. Seamless Tile Generator (S1) Make any image tileable: 23. Color Quantization Art (S1) Reduce colors for posterization/pixel art effect: 24. Animated GIF from Equation (S6) Generate mathematical art animations: 📊 GRAPHVIZ BEYOND DIAGRAMS 25. Music Theory Visualization (S4) Visualize chord progressions as graphs: 26. Git History as Art (S4) Turn git commit graphs into generative art: 27. Network Traffic Visualization (S4) Visualize packet flows as dynamic graphs: 28. Social Network from Email (S4) Parse email headers to visualize communication networks: 29. Directory Structure Art (S4) Visualize filesystem as artistic graph: 30. Algorithm Execution Trace (S4) Visualize sorting algorithms step-by-step: 📄 PANDOC TRANSFORMATIONS 31. Website to eBook Pipeline (S3) Convert any website to properly formatted EPUB: 32. Jupyter Notebook to Slideshow (S2) Convert data analysis to presentation: 33. Markdown to Mind Map (S3) Convert hierarchical markdown to visual mind map: 34. LaTeX to Accessible HTML (S2) Make academic papers accessible: 35. Multi-Format Documentation Generator (S2) Single source → PDF, HTML, DOCX, EPUB simultaneously: 36. CSV to Formatted Report (S3) Transform raw data to professional document: 🤖 MEDIAPIPE MAGIC 37. Pose-Controlled Video Effects (S3) Apply video effects based on body position: 38. Sign Language to Text (S3) Capture hand landmarks and translate gestures: 39. Virtual Background Without Green Screen (S1) MediaPipe selfie segmentation for custom backgrounds: 40. Exercise Form Analyzer (S3) Analyze workout form and provide feedback: 41. Puppet Animation from Webcam (S3) Control 2D characters with your body: 42. Gesture-Controlled Presentation (S3) Navigate slides with hand gestures: 43. Face Mesh to 3D Model (S3) Export facial geometry for 3D applications: 44. Attention Heatmap Generator (S3) Visualize where people look in videos: 🔬 OPENCV ALCHEMY 45. Document Scanner from Photo (S1) Automatic perspective correction: 46. Panorama Stitcher (S1) Create panoramas from overlapping images: 47. Motion Magnification (S1) Amplify subtle movements in video (Eulerian Video Magnification): 48. Invisible Watermark Embedding (S1) Hide data in images using DCT domain: 49. Photo to Pencil Sketch (S2) Realistic pencil drawing effect: 50. HDR from Single Image (S1) Fake HDR effect using tone mapping: 51. Object Removal (Inpainting) (S1) Remove unwanted objects from photos: 52. Real-time Edge Detection Art (S2) Stylized video with edge detection: 📈 DATA VISUALIZATION BEYOND CHARTS 53. Sound of Data (S5) Convert dataset to audio for pattern detection: Mind-blow: Hear anomalies in data that are invisible in charts! 54. Data-Driven Generative Art (S6) Use stock prices to generate abstract art: 55. Log File Music (S4) Transform server logs into ambient music: 56. Code Complexity Visualization (S4) Visualize codebase complexity as terrain: 57. Calendar Heatmap from Any Data (S6) GitHub-style contribution graph for anything: 58. Word Frequency Spiral (S6) Visualize text as logarithmic spiral: 59. Network Graph from Text (S4) Extract and visualize relationships from documents: 60. Animated Data Story (S3) Auto-generate data presentation videos: 🔤 TEXT & DOCUMENT MANIPULATION 61. PDF Layer Extraction (S1) Extract hidden layers from PDFs (comments, forms, annotations): 62. Document Diff Visualization (S3) Visual comparison of document versions: 63. Automatic Presentation from Outline (S3) Markdown outline → complete PPTX: 64. PDF Form Auto-Filler (S2) Template-based PDF form completion: 65. Book Chapter Splitter (S2) Split PDFs by table of contents: 66. Citation Network Extractor (S4) Build citation graph from academic PDFs: 67. Intelligent Document Merger (S2) Merge PDFs with automatic TOC generation: 68. Handwriting to Font (S3) Create custom font from handwriting sample: 🌐 WEB & AUTOMATION 69. Website Screenshot Timeline (S2) Document website evolution over time: 70. Automated A/B Testing Reporter (S3) Generate visual reports from test data: 71. Form to API Bridge (S3) Convert web forms to API endpoints: 72. Visual Regression Testing (S2) Compare screenshots for UI changes: 73. Web Archive to Offline Site (S3) Convert WARC files to browseable static site: 74. Automated Accessibility Audit (S3) Visual accessibility report generator: 🎵 AUDIO ENGINEERING 75. Vocal Isolation (S1) Extract vocals using phase cancellation: 76. Room Impulse Response Extraction (S2) Create reverb profiles from recordings: 77. Audio Time Stretching Without Pitch Change (S1) 78. Binaural Beat Generator (S1) Create meditation audio: 79. Audio Spectrum Analyzer Video (S2) Professional-looking spectrum analysis: 80. Cross-Correlation Audio Sync (S1) Automatically sync audio tracks: 🧮 MATHEMATICAL VISUALIZATION 81. LaTeX Equation to SVG (S2) Render equations as scalable graphics: 82. Symbolic Math Animation (S3) Animate mathematical derivations: 83. Function Plotter with Domain Coloring (S6) Visualize complex functions: 84. Parametric Equation Art (S6) Generate art from mathematical equations: 85. Geometric Transformation Visualizer (S3) Animate matrix transformations: 86. Prime Number Visualization (S6) Ulam spiral and other prime patterns: 87. Mathematical Knot Renderer (S6) 3D visualization of topological knots: 🔧 SYSTEM & DATA OPERATIONS 88. Binary File Visualization (S5) See patterns in any binary file: 89. Git Diff as Audio (S5) Hear your code changes: 90. Entropy Visualization (S4) See file randomness/compression potential: 91. Memory Dump Art (S5) Visualize process memory as images: 92. Log Rhythm (S4) Convert log timestamps to drum patterns: 93. File System Treemap (S4) Visualize disk usage artistically: 🎨 GENERATIVE & PROCEDURAL 94. Algorithmic Album Art (S6) Generate unique covers from audio analysis: 95. Text to Abstract Art (S4) Convert any text to unique visual: 96. Data-Driven Color Palettes (S4) Extract colors from datasets: 97. Procedural Texture Generator (S6) Create tileable textures algorithmically: 98. Generative Music from Images (S5) Convert images to music: 99. Chaos Game Visualizations (S6) Generate fractals from simple rules: 100. L-System Plant Generator (S6) Create botanical illustrations algorithmically: 🔀 CROSS-TOOL MEGA-WORKFLOWS 101. Podcast to Visual Summary (S3) Audio → Transcript → Key points → Infographic: 102. Codebase Documentary (S3) Generate video documentation from code: 103. Photo Collection to Video Story (S3) EXIF data + images → narrative video: 104. Data Pipeline Visualization (S4) Auto-document ETL processes: 105. Meeting Notes to Action Items (S3) Audio → Tasks → Calendar events: 106. Interactive Data Explorer Generator (S3) CSV → Full web application: 107. Research Paper to Presentation (S3) PDF → Slide deck automatically: 108. Video to Comic Strip (S3) Extract key frames → comic layout: 109. Music Video Auto-Generator (S3) Audio analysis → synchronized visuals: 110. Automated Documentation Site (S3) Code + docstrings → full documentation website: 🌟 EXPERIMENTAL & AVANT-GARDE 111. Synesthetic Experience Generator (S5) Any data → All senses representation: 112. Quantum-Inspired Art (S6) Superposition visualizations: 113. Neural Network Weight Visualizer (S4) See inside ML models: 114. Time Crystal Visualization (S6) Periodic structures in time domain: 115. Emergence Simulator (S6) Visualize emergent behavior from simple rules: 116. Linguistic DNA (S4) Visualize language structure like genetic sequences: 117. Architectural Space from Text (S4) Convert descriptions to 3D floorplans: 118. Dream Journal Visualizer (S4) Text analysis to surreal imagery: 119. Temporal Code Archaeology (S4) Visualize how code evolved: 120. Musical Genome (S4) DNA-style representation of songs: 🚀 META-OPERATIONS 121. Tool Capability Mapper (S7) Auto-discover tool features: 122. Workflow Optimizer (S7) Analyze and optimize shell pipelines: 123. Cross-Tool Format Bridge (S7) Auto-generate converters between any formats: 124. Self-Documenting Scripts (S7) Generate documentation from tool usage: 125. Reproducibility Packager (S7) Package any analysis for reproducibility: 📋 QUICK REFERENCE: Verified Commands All FFmpeg filters verified via ffmpeg -filters: ✅ mandelbrot, life, sierpinski, cellauto (generative) ✅ showwaves, showspectrum, showcqt, showfreqs, a3dscope, avectorscope, aphasemeter (audio viz) ✅ blend, overlay, chromakey, drawtext, rotate, vignette (video effects) ✅ hstack, vstack, xstack, tile, concat (layout) ✅ afir, atempo, areverse (audio processing) ImageMagick operations verified via convert -list: ✅ -morphology, -distort, -fft, -colors, -dither Python libraries verified installed: ✅ mediapipe (facedetection, facemesh, hands, pose, holistic, selfiesegmentation) ✅ opencv-python (cv2) ✅ scikit-image ✅ networkx (936 graph functions) ✅ sympy, matplotlib, seaborn, pandas, numpy ✅ playwright, beautifulsoup4, pillow ✅ pdfplumber, pypdf, pikepdf, reportlab ✅ python-docx, python-pptx, openpyxl Document tools verified: ✅ pandoc (40+ input formats, 30+ output formats) ✅ pdflatex, xelatex ✅ pdftk, qpdf ✅ tesseract (OCR) ✅ libreoffice Graphviz layouts verified: ✅ dot, neato, fdp, sfdp, circo, twopi, osage, patchwork Generated by exploring the hidden depths of standard tools. Each idea is a doorway to creative possibilities. ChatGPT's ideas Original ChatGPT conversation Mind-bending workflows you can build from “boring” tools You noticed the pattern: complex tools hide entire product lines behind obscure flags. This file is a catalog of ways to discover, combine, and weaponize those hidden capabilities. What’s installed here (spot‑checked) ffmpeg — audio/video processing; includes audio visualization filters, procedural generators (mandelbrot, life, cellauto), flite TTS, pocketsphinx ASR, chromaprint fingerprints ImageMagick — image processing, compositing, compare diffs, montage contact sheets Poppler — pdftotext/pdftoppm/pdftocairo/pdfimages/pdfunite/pdfseparate/pdffonts/pdfinfo Ghostscript — PDF transform/compress/rasterize Pandoc — convert between markdown/html/docx/pptx/pdf, slide decks (reveal.js, pptx) Tesseract — OCR to text or PDF Inkscape — SVG PDF/PNG convert, CLI batch operations Graphviz — diagram generation (dot/neato/fdp/sfdp) SoX — audio transform/effects; lacks png handler here but still useful Python 3.11 — scripting + reportlab/python-docx/openpyxl etc Node 22 — scripting + pptxgenjs etc Git/Make/GCC — reproducible pipelines, small native utilities Spot-checks performed (so the ideas don’t rely on wishful thinking) FFmpeg audio-visualization filters present: showcqt, showfreqs, showspectrum, showspectrumpic, showwaves, showwavespic, avectorscope, aphasemeter, ahistogram. FFmpeg contains TTS source filter flite (options include text, textfile, voice). FFmpeg contains offline ASR filter asr (Pocketsphinx-style: hmm, dict, lm). FFmpeg supports Chromaprint muxer (-f chromaprint) with base64 output. Poppler tools confirmed: pdftotext, pdftoppm, pdftocairo, pdfimages, pdfunite, pdfseparate, pdffonts, pdfinfo. ImageMagick tools confirmed: magick, montage, compare. Inkscape CLI confirmed. Strategies for discovering “hidden capabilities” 1. Abuse the tool as a generator, not a transformer — Many tools can synthesize data (e.g., FFmpeg’s mandelbrot, life, cellauto, and TTS flite). Treat them as procedural engines. 2. Look for analysis outputs masquerading as side effects — Tools that print stats/logs (ffmpeg filters like silencedetect, blackdetect, ebur128, astats) can become your feature extractor. 3. Round‑trip conversions to unlock a missing feature — If one tool can export a rich intermediate (SVG/PDF/frames), another tool can “do the thing” (diff, OCR, layout, animation). 4. Turn everything into a timeline — Audio/video timelines are the universal container: text overlays, chapters, subtitles, thumbnails, “data movies”. 5. Automate contacts sheets and diffs — A “before/after/changed” visual is often more useful than metrics. ImageMagick + FFmpeg + Poppler can make diffs for anything. 6. Exploit “single‑file delivery” formats — MP4/MKV/WEBM can carry video+audio+subtitles+chapters+attachments. PDF can carry images+text+forms. Package your pipeline outputs into one portable artifact. 7. Use metadata as a covert channel — Hashes, prompts, provenance, settings: embed in file metadata (media tags, PDF info). Makes pipelines self‑documenting. 8. Treat CLI programs as a “DSP / graphics shader graph” — FFmpeg filtergraphs and ImageMagick pipelines are essentially node graphs. Compose them like modular synth patches. 9. Design “one command = one artifact” — Make outputs easy to evaluate: one MP4 per idea, one PDF per report, one HTML per dashboard. This makes AI exploration cheap. 10. Make evaluators first-class — Every creative pipeline should have a cheap ‘is it good?’ check: loudness report, frame diff heatmap, OCR confidence, page count, etc. 11. Cache intermediates aggressively — Split pipelines into stages; keep intermediate files for inspection and reuse. 12. Parameterize like a product — Every pipeline becomes reusable when it accepts {input, style, seed, duration, output}. Idea catalog (long, concrete, command‑shaped) All commands are sketches, not copy‑paste promises. Capabilities were cursorily verified via tool help/feature lists in this environment (e.g., FFmpeg has showcqt, showspectrum, avectorscope, ahistogram, flite, asr, chromaprint). 1. Audio → narrated explainer video with zero external TTS What it unlocks: Turn a text script into speech using FFmpeg’s built-in flite, then generate visuals (spectra, waveforms, fractals) and overlay titles/subtitles. Tools: ffmpeg Sketch: ffmpeg -f lavfi -i "flite=textfile=script.txt:voice=kal" -f lavfi -i "mandelbrot=s=1280x720:r=30" -filtercomplex "[0:a]showcqt=s=1280x360[viz];[1:v][viz]vstack" -shortest out.mp4 Notes: Mind-bender: FFmpeg includes a TTS source filter (flite). 2. Offline speech‑to‑text inside FFmpeg (Pocketsphinx ASR) What it unlocks: Use FFmpeg’s asr filter to run offline ASR (needs acoustic model + dict + LM). Dump transcripts via logs/metadata for fast rough captions. Tools: ffmpeg Sketch: ffmpeg -i talk.wav -af "asr=hmm=MODEL:dict=cmudict-en-us.dict:lm=en-us.lm" -f null - Notes: This is ‘rough but local’ captioning; great for quick indexing. 3. Audio fingerprinting pipeline (Chromaprint) for de‑dup + matching What it unlocks: Generate Chromaprint fingerprints to detect duplicates, identify repeated hooks, or build a ‘find similar clips’ index. Tools: ffmpeg + python/node Sketch: ffmpeg -i input.mp3 -f chromaprint -fpformat base64 - | tee fp.txt Notes: Works without external tools; the output is small and indexable. 4. Silence‑aware chaptering + auto‑cut reels What it unlocks: Detect silences (silencedetect) to cut podcasts/lectures into logical segments; export chapters + separate clips. Tools: ffmpeg + python Sketch: ffmpeg -i in.wav -af silencedetect=noise=-35dB:d=0.4 -f null - 2> silences.log Notes: Parse silences.log to compute cut points. 5. Black‑frame + freeze detection to auto‑remove dead air in screen recordings What it unlocks: Detect ‘nothing happening’ via blackdetect and freezedetect, then auto-skip or accelerate those sections. Tools: ffmpeg Sketch: ffmpeg -i screen.mp4 -vf blackdetect=d=0.4:pixth=0.1 -an -f null - 2> black.log Notes: Turn boring demos into tight ‘no-waiting’ tutorials. 6. One input → many outputs at once (tee muxer) What it unlocks: Encode one time, emit MP4 + GIF + thumbnails + audio-only + loudness report in a single run. Tools: ffmpeg Sketch: ffmpeg -i in.mp4 -filtercomplex "[0:v]fps=15,scale=480:-1[vgif];[0:v]thumbnail,scale=320:-1[vthumb]" -map 0:v -map 0:a -f tee "[f=mp4]out.mp4|[f=gif]out.gif" Notes: Great for ‘publish everywhere’ automation. 7. Auto contact-sheet / storyboard from any video (tile filter) What it unlocks: Sample frames and tile them into a single image for quick preview or QA review. Tools: ffmpeg Sketch: ffmpeg -i in.mp4 -vf "select='not(mod(n,60))',scale=320:-1,tile=6x4" -frames:v 1 storyboard.png Notes: Perfect for scanning long videos fast. 8. Scene-change detection → “highlights only” cut What it unlocks: Use FFmpeg’s scene detection via select to pull only high-change moments; great for sports, talks, screencasts. Tools: ffmpeg Sketch: ffmpeg -i in.mp4 -vf "select='gt(scene,0.35)',showinfo" -vsync vfr -framepts 1 frames/%06d.png Notes: Then assemble highlights into a reel. 9. Procedural animation engine (fractal/life/cellauto) synced to audio What it unlocks: Generate mesmerizing visuals without any assets using mandelbrot, life, cellauto, etc., and drive parameters over time. Tools: ffmpeg Sketch: ffmpeg -f lavfi -i "life=s=1280x720:r=30:mold=3" -i song.wav -shortest out.mp4 Notes: Generative art with no dependencies. 10. GPU-ish look using libplacebo + tone mapping (even on SDR sources) What it unlocks: Apply high-quality scaling and filmic tone mapping with libplacebo / tonemap for ‘premium’ visuals. Tools: ffmpeg Sketch: ffmpeg -i in.mp4 -vf "libplacebo=upscaler=ewalanczos;tonemap" out.mp4 Notes: Useful for upscaling old footage. 11. Data-in-video: embed JSON payloads in subtitles track What it unlocks: Store structured data (timestamps, labels, scores) inside an MP4/MKV as a subtitle track (WebVTT/ASS) so the video is self-describing. Tools: ffmpeg + python/node Sketch: ffmpeg -i in.mp4 -i labels.vtt -c copy -c:s movtext labeled.mp4 Notes: You can later extract + parse labels.vtt. 12. Visual QA: generate a ‘diff video’ between two renders What it unlocks: Overlay absolute difference between two videos to spot subtle regressions (color shifts, dropped frames). Tools: ffmpeg Sketch: ffmpeg -i a.mp4 -i b.mp4 -filtercomplex "[0:v][1:v]blend=allmode=difference" diff.mp4 Notes: A unit test for creative pipelines. 13. Audio QA: loudness normalization + compliance report (EBU R128) What it unlocks: Generate a loudness report with ebur128, then normalize audio for consistent perceived volume. Tools: ffmpeg Sketch: ffmpeg -i in.wav -af ebur128=peak=true -f null - 2> loudness.log Notes: Turn loudness into a CI check. 14. Make a lecture searchable without ASR: ‘acoustic indexing’ via chromaprint + silence What it unlocks: Even without transcription, fingerprints + silence segmentation give you an index: repeated motifs, Q&A sections, music cues. Tools: ffmpeg + python Notes: Good when full ASR is unavailable or privacy-sensitive. 15. Build ‘karaoke mode’ without vocals isolation What it unlocks: Use EQ + mid/side tricks to attenuate center channel vocals; not perfect, but fast and sometimes surprisingly effective. Tools: ffmpeg Sketch: ffmpeg -i song.mp3 -af "pan=stereo|c0=c0-c1|c1=c1-c0" karaoke-ish.wav Notes: Works best on stereo mixes with centered vocals. 16. Audio-driven typography What it unlocks: Animate words (ASS subtitles) with per-word timing; overlay on abstract visuals. Tools: ffmpeg + ASS subtitles Sketch: ffmpeg -i bg.mp4 -vf "subtitles=words.ass" out.mp4 17. Auto-generate ‘music visualizer pack’ as a template What it unlocks: One input WAV, outputs 20 styles (showcqt, showfreqs, ahistogram, vstack grids). Tools: ffmpeg + make 18. Build an ‘audio microscope’ clip What it unlocks: Stack multiple analysis views (waveform + spectrum + vectorscope + loudness meter) into one diagnostic video. Tools: ffmpeg Sketch: ffmpeg -i in.wav -filtercomplex "[0:a]showwaves=s=1280x240[w];[0:a]showspectrum=s=1280x240[sp];[0:a]avectorscope=s=640x480[vs];[w][sp]vstack[top];[top][vs]vstack" out.mp4 19. Turn any image into a Ken Burns documentary with auto-captions What it unlocks: Zoom/pan + text overlays from a CSV of captions. Tools: ffmpeg + python 20. GIF factory with smart palette What it unlocks: High-quality GIFs via palettegen/paletteuse. Tools: ffmpeg Sketch: ffmpeg -i in.mp4 -vf "fps=15,scale=480:-1:flags=lanczos,palettegen" -y pal.png && ffmpeg -i in.mp4 -i pal.png -lavfi "fps=15,scale=480:-1:flags=lanczos[x];[x][1:v]paletteuse" out.gif 21. Meme subtitle burner that never looks amateur What it unlocks: Use ASS styling (shadows, outlines) with subtitles filter. Tools: ffmpeg + libass Sketch: ffmpeg -i in.mp4 -vf "subtitles=meme.ass" out.mp4 22. Auto-summarize video visually What it unlocks: Pick representative frames with thumbnail + tile them; attach as cover image. Tools: ffmpeg Sketch: ffmpeg -i in.mp4 -vf "thumbnail,scale=320:-1,tile=5x5" -frames:v 1 summary.png 23. Temporal ‘x-ray’ of motion What it unlocks: Use blend modes to accumulate motion trails across time. Tools: ffmpeg Sketch: ffmpeg -i in.mp4 -vf "tmix=frames=8:weights='1 1 1 1 1 1 1 1'" trails.mp4 24. Optical-flow style smoothing What it unlocks: Use minterpolate to create buttery 60fps or slow-motion. Tools: ffmpeg Sketch: ffmpeg -i in.mp4 -vf "minterpolate=fps=60" smooth.mp4 25. 360° video rebuilder What it unlocks: Use v360 to convert projections for VR content workflows. Tools: ffmpeg Sketch: ffmpeg -i in360.mp4 -vf "v360=input=equirect:output=flat" flat.mp4 26. Batch ‘audio watermark’ What it unlocks: Embed an inaudible-ish watermark tone pattern at low level; later detect via spectrogram. Tools: ffmpeg 27. ‘Podcast thumbnail’ generator What it unlocks: Extract a face frame + add waveform overlay + title card. Tools: ffmpeg + ImageMagick 28. Video chapters from a text outline What it unlocks: Map outline timestamps into MP4 chapters metadata. Tools: ffmpeg 29. Lossless clip extraction with sample-accurate boundaries What it unlocks: Use -ss/-to with stream copy where possible; fallback to re-encode. Tools: ffmpeg 30. Transcode matrix: one master → multiple bitrates/resolutions What it unlocks: Create ABR ladder outputs. Tools: ffmpeg Sketch: ffmpeg -i in.mp4 -filtercomplex "[0:v]split=3[v1][v2][v3];[v1]scale=1920:-1[v1o];[v2]scale=1280:-1[v2o];[v3]scale=854:-1[v3o]" -map "[v1o]" -map 0:a out1080.mp4 -map "[v2o]" -map 0:a out720.mp4 -map "[v3o]" -map 0:a out480.mp4 31. Self-contained ‘dataset video’ What it unlocks: Encode a timeseries as scrolling plot video; store the CSV in metadata/subtitles. Tools: python + ffmpeg 32. PDF visual regression testing What it unlocks: Convert PDFs to images and produce a heatmap diff to catch tiny layout changes (fonts, margins, pagination). Tools: pdftoppm + ImageMagick compare Sketch: pdftoppm -png a.pdf a/page && pdftoppm -png b.pdf b/page && compare -metric AE a/page-1.png b/page-1.png diff.png Notes: Turns document rendering into CI-friendly tests. 33. OCR-first PDF search index What it unlocks: Rasterize PDF pages, OCR with Tesseract, store text + coordinates for fast local search. Tools: pdftoppm + tesseract + python Sketch: pdftoppm -png doc.pdf pages/page && tesseract pages/page-1.png ocr/page-1 -l eng tsv Notes: TSV gives word-level bounding boxes. 34. Extract embedded images from PDFs (no OCR) What it unlocks: Pull original images via pdfimages for reuse or forensic inspection. Tools: pdfimages Sketch: pdfimages -all doc.pdf extracted/img Notes: Great for reverse-engineering slide decks. 35. PDF → editable SVG per page What it unlocks: Convert each PDF page into SVG, then edit in Inkscape or post-process as XML. Tools: pdftocairo + inkscape Sketch: pdftocairo -svg doc.pdf pages/page && inkscape pages/page-1.svg --export-type=png --export-filename=page1.png Notes: SVG gives you structure; surprisingly hackable. 36. Markdown → PPTX with a house style (Pandoc reference PPTX) What it unlocks: Generate consistent corporate decks automatically by using a template PPTX as style reference. Tools: pandoc Sketch: pandoc deck.md -t pptx --reference-doc=template.pptx -o deck.pptx Notes: Instant ‘slides as code’ workflow. 37. Markdown → PDF with diagrams baked in What it unlocks: Use Pandoc + Graphviz: generate diagrams to SVG/PNG, embed, and output PDF. Tools: pandoc + graphviz + inkscape Notes: Make documentation build like software. 38. Generate ‘living docs’ from code + tests What it unlocks: Run scripts to produce charts/images, then Pandoc stitches into a docx/pdf report on every run. Tools: python + pandoc Notes: A reproducible report factory. 39. PDF page surgery (split / reorder / merge) without Acrobat What it unlocks: Split a PDF into pages, reorder, then merge back. Tools: pdfseparate + pdfunite Sketch: pdfseparate in.pdf out-%d.pdf && pdfunite out-3.pdf out-1.pdf out-2.pdf reordered.pdf Notes: Fast batch manipulation. 40. Compress and ‘web-optimize’ PDFs via Ghostscript What it unlocks: Shrink file size and standardize output for delivery. Tools: gs Sketch: gs -sDEVICE=pdfwrite -dCompatibilityLevel=1.4 -dPDFSETTINGS=/ebook -dNOPAUSE -dBATCH -sOutputFile=small.pdf in.pdf Notes: Useful when sending big scanned docs. 41. Document ‘time-lapse’: diff between revisions as a flipbook GIF What it unlocks: Render each revision to images, then animate differences to show what changed over time. Tools: pdftoppm + ImageMagick Notes: Visual storytelling for document edits. 42. ImageMagick as a layout engine for ‘poster-like’ composites What it unlocks: Generate magazine-style compositions (grids, captions, drop shadows) from a folder of assets. Tools: ImageMagick Sketch: magick montage frames/.png -geometry 320x180+10+10 -tile 4x3 montage.png Notes: Build ‘visual dashboards’ without a GUI. 43. Instant ‘visual unit tests’ for images What it unlocks: Use compare with metrics (AE, RMSE, PSNR) to flag regressions in generated images. Tools: ImageMagick compare Sketch: compare -metric RMSE a.png b.png diff.png 2> metrics.txt Notes: Plug into CI; fail build on too much change. 44. SVG templating for data-driven visuals What it unlocks: Use SVG as a template; fill text/values via a small script; export high-res PNG/PDF via Inkscape. Tools: Inkscape + python/node Sketch: inkscape template.svg --export-type=png --export-filename=out.png --export-dpi=300 Notes: Turns vector design into programmable output. 45. Graphviz → animated ‘graph growth’ video What it unlocks: Generate DOT snapshots over time, render to SVG/PNG, then FFmpeg them into an animation. Tools: graphviz + inkscape + ffmpeg Notes: Perfect for explaining evolving networks. 46. Auto-generate architecture diagrams from a directory tree What it unlocks: Walk a repo, emit DOT edges (folder → file), render with Graphviz. Tools: python + graphviz Notes: A repo becomes a map. 47. Design once, export everywhere: SVG → PDF → PPTX What it unlocks: Use Inkscape to export PDFs/PNGs, then Pandoc/PPTXGenJS to embed as slides. Tools: inkscape + pandoc + node(pptxgenjs) Notes: Vector-first slide workflow. 48. ‘Data comic strips’ generator What it unlocks: Use ImageMagick to compose panels, speech bubbles; use Pandoc to produce PDF booklets. Tools: ImageMagick + pandoc Notes: A playful reporting format. 49. Turn screenshots into editable docs (OCR → DOCX) What it unlocks: OCR images to text, then Pandoc to DOCX, preserving headings via heuristics. Tools: tesseract + pandoc + python Notes: Quick ‘I only have screenshots’ rescue workflow. 50. Whiteboard / slide capture to searchable PDF What it unlocks: Extract frames from video, choose sharp frames, OCR, and assemble into a PDF for search. Tools: ffmpeg + tesseract + pdfunite Notes: A lecture becomes a document. 51. Auto-redact PDFs by locating keywords via OCR coordinates What it unlocks: OCR to TSV, locate sensitive tokens, draw opaque rectangles on page images, reassemble PDF. Tools: pdftoppm + tesseract + ImageMagick + pdfunite Notes: Privacy tooling without proprietary software. 52. Single-command ‘research bundle’ builder What it unlocks: Given a folder, produce: README, checksums, contact sheet, OCR text, and a single PDF/HTML index. Tools: make + python + pandoc + ImageMagick + poppler Notes: Great for audits and handoffs. 53. Provenance stamping everywhere What it unlocks: Embed git commit hash + tool versions into video metadata, PDF info, and slide notes automatically. Tools: git + ffmpeg + gs/pandoc Sketch: ffmpeg -i in.mp4 -metadata comment="git:$GITCOMMIT" -c copy out.mp4 Notes: Your artifacts become self-auditing. 54. Audio ‘style transfer’ without ML: effect chains as presets What it unlocks: Create cinematic audio signatures using SoX effect chains (reverb, compand, EQ) and package as presets. Tools: sox + ffmpeg Sketch: sox in.wav out.wav compand 0.3,1 6:-70,-60,-20 -5 -90 0.2 reverb 40 Notes: A surprisingly large creative space lives here. 55. Dataset sonification + visualization What it unlocks: Map a timeseries to pitch/volume and render as audio; then visualize with FFmpeg (CQT/spectrum) as an explainer. Tools: python + sox/ffmpeg Notes: Data storytelling you can hear. 56. PDF font forensics report What it unlocks: List fonts used in a PDF (pdffonts), flag non-embedded fonts, and generate a QA report. Tools: pdffonts + python/pandoc Sketch: pdffonts doc.pdf > fonts.txt 57. Image metadata scrubbing for privacy What it unlocks: Strip metadata from images before sharing. Tools: ImageMagick Sketch: magick in.jpg -strip out.jpg 58. Instant ‘book scan’ cleanup What it unlocks: Deskew/threshold/denoise scanned pages, then OCR. Tools: ImageMagick + tesseract Sketch: magick in.png -deskew 40% -threshold 55% clean.png 59. PDF posterizer What it unlocks: Turn each PDF page into a high-res poster PNG set. Tools: pdftocairo Sketch: pdftocairo -png -r 300 doc.pdf poster/page 60. Auto-generate YouTube-style chapter markers What it unlocks: Use silence + scene detection to propose chapters. Tools: ffmpeg + python 61. Spectral ‘signature’ thumbnails for audio files What it unlocks: Create a tiny showspectrumpic image per track; use as album ‘barcode’. Tools: ffmpeg Sketch: ffmpeg -i song.mp3 -lavfi showspectrumpic=s=800x200 out.png -frames:v 1 62. Waveform spritesheets What it unlocks: Generate waveform images for web audio players. Tools: ffmpeg Sketch: ffmpeg -i song.mp3 -lavfi showwavespic=s=1200x200 out.png -frames:v 1 63. Audio QA dashboard video What it unlocks: Concatenate multiple visualization styles with title cards (your discovery). Tools: ffmpeg 64. ‘Explain the mix’: mid/side breakdown What it unlocks: Convert audio to mid/side channels and visualize each. Tools: ffmpeg 65. Auto ‘speaker separation-ish’ What it unlocks: Not real diarization, but split by volume/frequency bands and visualize; sometimes enough for rough segmentation. Tools: ffmpeg 66. Subtitle → animated kinetic typography What it unlocks: Render subtitles with per-word timing into a typographic video. Tools: ffmpeg + ASS 67. Batch convert DOCX ↔ Markdown What it unlocks: Roundtrip documents for diff-friendly reviews in git. Tools: pandoc + git Sketch: pandoc in.docx -t gfm -o in.md 68. Slide deck linting What it unlocks: Convert PPTX → PDF/PNG and run visual diff between builds. Tools: pandoc + poppler + ImageMagick 69. Extract every image/video from a PPTX What it unlocks: PPTX is a ZIP; extract media assets for reuse. Tools: python/node 70. Make a ‘single-file website’ report What it unlocks: Pandoc to standalone HTML; embed images and CSS. Tools: pandoc Sketch: pandoc report.md -s --embed-resources -o report.html 71. Diagram-as-code to slides What it unlocks: Generate Graphviz SVGs; insert into PPTX on build. Tools: graphviz + pandoc 72. SVG diffing What it unlocks: Render two SVGs to PNG and compare; flags pixel changes reliably. Tools: inkscape + compare Sketch: inkscape a.svg --export-filename=a.png && inkscape b.svg --export-filename=b.png && compare a.png b.png diff.png 73. Media ‘manifest’ generator What it unlocks: For a folder of media, run ffprobe to JSON, then build an index HTML. Tools: ffprobe + python/node Sketch: ffprobe -v error -showformat -showstreams -of json in.mp4 > meta.json 74. Detect duplicated frames What it unlocks: Use mpdecimate to detect/strip near-duplicates (bad screen capture). Tools: ffmpeg Sketch: ffmpeg -i in.mp4 -vf mpdecimate -an out.mp4 75. Automatic de-interlacing with quality checks What it unlocks: Use yadif/bwdif and compare against original. Tools: ffmpeg 76. Build a ‘visual diff’ for two PDFs across all pages What it unlocks: Loop pages, compare, output a single diff PDF. Tools: poppler + ImageMagick + pdfunite 77. Turn CSV into a deck automatically What it unlocks: Python generates markdown slides; Pandoc emits PPTX. Tools: python + pandoc 78. Instant icon set from SVGs What it unlocks: Batch export SVG icons to multiple PNG sizes. Tools: inkscape Sketch: for s in 16 32 64 128; do inkscape icon.svg --export-width=$s --export-filename=icon-$s.png; done 79. Color palette extraction from video What it unlocks: Sample frames; ImageMagick quantize; produce palette swatches. Tools: ffmpeg + ImageMagick 80. Make animated stickers What it unlocks: Trim, loop, scale, add transparency; output WebM with alpha where possible. Tools: ffmpeg 81. Turn a folder of images into a narrated slideshow What it unlocks: FFmpeg for video, flite for narration, subtitle overlays for labels. Tools: ffmpeg 82. Auto-censor profanity in audio What it unlocks: Detect timecodes (from transcript or manual list), then attenuate or beep. Tools: ffmpeg 83. Generate a ‘data watermark’ as a barely-visible steganographic overlay What it unlocks: Encode an ID in subtle pixel patterns across frames. Tools: ffmpeg 84. Build a ‘clip library’ with visual thumbnails What it unlocks: Extract 1s previews + poster frames + metadata JSON. Tools: ffmpeg + ffprobe 85. Create ‘video sprites’ for web scrubbing What it unlocks: Generate a grid of thumbnails at intervals (seek preview). Tools: ffmpeg 86. Convert any diagram to a ‘hand-drawn’ look What it unlocks: Use ImageMagick sketch/charcoal + noise, then re-vectorize if needed. Tools: ImageMagick + inkscape 87. Turn PDFs into audiobooks (rough) What it unlocks: Extract text with pdftotext, then speak with FFmpeg flite. Tools: pdftotext + ffmpeg 88. PDF indexer with clickable timestamps What it unlocks: Create an HTML index linking to PDF pages + extracted key phrases. Tools: poppler + python 89. Interactive reveal.js decks from Markdown + embedded videos What it unlocks: Pandoc to revealjs; FFmpeg generates embedded demo videos. Tools: pandoc + ffmpeg 90. Make a searchable screenshot atlas for a long app demo What it unlocks: Extract keyframes, OCR, build an HTML search UI. Tools: ffmpeg + tesseract + node 91. OCR confidence heatmap What it unlocks: Visualize OCR uncertainty by overlaying colored boxes over the original page. Tools: tesseract + ImageMagick 92. ‘Explain a codebase’ poster What it unlocks: Graphviz renders module graph; Inkscape styles; output as PDF poster. Tools: graphviz + inkscape 93. One-command ‘talk to slides’ converter What it unlocks: Video → frames → OCR headings → auto outline → PPTX. Tools: ffmpeg + tesseract + pandoc 94. Batch generate animated lower-thirds What it unlocks: Create transparent animated overlays for names/titles. Tools: ffmpeg + ImageMagick 95. Audio peak finder for ‘best 12 seconds’ teaser What it unlocks: Find loudest segment; cut; generate a teaser video. Tools: ffmpeg + python 96. Compute ‘attention map’ from motion + audio energy What it unlocks: Estimate excitement from motion intensity + audio RMS; visualize as timeline. Tools: ffmpeg + python 97. Auto-generate subtitles from script file timing What it unlocks: Convert a transcript with timestamps to VTT, embed. Tools: python + ffmpeg 98. Replace greenscreen without NLE What it unlocks: Use chromakey + background replacement, add spill suppression. Tools: ffmpeg 99. Batch watermark images/videos with consistent design What it unlocks: Use ImageMagick for images; FFmpeg for video. Tools: ImageMagick + ffmpeg 100. Build a ‘PDF to slide thumbnails’ contact sheet What it unlocks: Render each page to PNG, then montage into a quick overview sheet. Tools: pdftoppm + montage 101. Language-agnostic OCR What it unlocks: Switch tesseract languages per file; build multilingual search index. Tools: tesseract 102. ‘Layout debugger’ for PDFs What it unlocks: Extract bounding boxes from OCR TSV and draw them to see reading order issues. Tools: tesseract + ImageMagick 103. Text-to-ASCII-art video What it unlocks: Render frames to ASCII (ImageMagick) and encode to video. Tools: ImageMagick + ffmpeg 104. Convert SVG animations to MP4 What it unlocks: Render SVG frames or use inkscape export to create videos. Tools: inkscape + ffmpeg 105. Make a ‘font specimen’ PDF from installed fonts What it unlocks: Enumerate fonts, render sample text, produce PDF. Tools: python + reportlab 106. Visual diff pipeline for video What it unlocks: Render A and B, compute diff heatmap, package into a PDF report. Applied to video. Tools: ffmpeg + ffprobe + ImageMagick Notes: Template idea; fill with your specific constraints. 107. Visual diff pipeline for audio What it unlocks: Render A and B, compute diff heatmap, package into a PDF report. Applied to audio. Tools: ffmpeg + sox Notes: Template idea; fill with your specific constraints. 108. Visual diff pipeline for PDF What it unlocks: Render A and B, compute diff heatmap, package into a PDF report. Applied to PDF. Tools: poppler + ImageMagick Notes: Template idea; fill with your specific constraints. 109. Visual diff pipeline for SVG What it unlocks: Render A and B, compute diff heatmap, package into a PDF report. Applied to SVG. Tools: inkscape + ImageMagick Notes: Template idea; fill with your specific constraints. 110. Visual diff pipeline for slides (PPTX) What it unlocks: Render A and B, compute diff heatmap, package into a PDF report. Applied to slides (PPTX). Tools: pandoc + poppler Notes: Template idea; fill with your specific constraints. 111. Contact sheet pipeline for video What it unlocks: Summarize long media by tiling representative frames/pages. Applied to video. Tools: ffmpeg + ffprobe + ImageMagick Notes: Template idea; fill with your specific constraints. 112. Contact sheet pipeline for audio What it unlocks: Summarize long media by tiling representative frames/pages. Applied to audio. Tools: ffmpeg + sox Notes: Template idea; fill with your specific constraints. 113. Contact sheet pipeline for PDF What it unlocks: Summarize long media by tiling representative frames/pages. Applied to PDF. Tools: poppler + ImageMagick Notes: Template idea; fill with your specific constraints. 114. Contact sheet pipeline for SVG What it unlocks: Summarize long media by tiling representative frames/pages. Applied to SVG. Tools: inkscape + ImageMagick Notes: Template idea; fill with your specific constraints. 115. Contact sheet pipeline for slides (PPTX) What it unlocks: Summarize long media by tiling representative frames/pages. Applied to slides (PPTX). Tools: pandoc + poppler Notes: Template idea; fill with your specific constraints. 116. Search index pipeline for video What it unlocks: Extract text/OCR + metadata, build a tiny HTML search UI. Applied to video. Tools: ffmpeg + ffprobe + ImageMagick Notes: Template idea; fill with your specific constraints. 117. Search index pipeline for audio What it unlocks: Extract text/OCR + metadata, build a tiny HTML search UI. Applied to audio. Tools: ffmpeg + sox Notes: Template idea; fill with your specific constraints. 118. Search index pipeline for PDF What it unlocks: Extract text/OCR + metadata, build a tiny HTML search UI. Applied to PDF. Tools: poppler + ImageMagick Notes: Template idea; fill with your specific constraints. 119. Search index pipeline for SVG What it unlocks: Extract text/OCR + metadata, build a tiny HTML search UI. Applied to SVG. Tools: inkscape + ImageMagick Notes: Template idea; fill with your specific constraints. 120. Search index pipeline for slides (PPTX) What it unlocks: Extract text/OCR + metadata, build a tiny HTML search UI. Applied to slides (PPTX). Tools: pandoc + poppler Notes: Template idea; fill with your specific constraints. 121. Provenance embed pipeline for video What it unlocks: Embed prompts/settings/hashes into metadata + sidecar JSON. Applied to video. Tools: ffmpeg + ffprobe + ImageMagick Notes: Template idea; fill with your specific constraints. 122. Provenance embed pipeline for audio What it unlocks: Embed prompts/settings/hashes into metadata + sidecar JSON. Applied to audio. Tools: ffmpeg + sox Notes: Template idea; fill with your specific constraints. 123. Provenance embed pipeline for PDF What it unlocks: Embed prompts/settings/hashes into metadata + sidecar JSON. Applied to PDF. Tools: poppler + ImageMagick Notes: Template idea; fill with your specific constraints. 124. Provenance embed pipeline for SVG What it unlocks: Embed prompts/settings/hashes into metadata + sidecar JSON. Applied to SVG. Tools: inkscape + ImageMagick Notes: Template idea; fill with your specific constraints. 125. Provenance embed pipeline for slides (PPTX) What it unlocks: Embed prompts/settings/hashes into metadata + sidecar JSON. Applied to slides (PPTX). Tools: pandoc + poppler Notes: Template idea; fill with your specific constraints. 126. Timeline markers pipeline for video What it unlocks: Detect events (silence/black/scene) and output chapters/markers. Applied to video. Tools: ffmpeg + ffprobe + ImageMagick Notes: Template idea; fill with your specific constraints. 127. Timeline markers pipeline for audio What it unlocks: Detect events (silence/black/scene) and output chapters/markers. Applied to audio. Tools: ffmpeg + sox Notes: Template idea; fill with your specific constraints. 128. Timeline markers pipeline for PDF What it unlocks: Detect events (silence/black/scene) and output chapters/markers. Applied to PDF. Tools: poppler + ImageMagick Notes: Template idea; fill with your specific constraints. 129. Timeline markers pipeline for SVG What it unlocks: Detect events (silence/black/scene) and output chapters/markers. Applied to SVG. Tools: inkscape + ImageMagick Notes: Template idea; fill with your specific constraints. 130. Timeline markers pipeline for slides (PPTX) What it unlocks: Detect events (silence/black/scene) and output chapters/markers. Applied to slides (PPTX). Tools: pandoc + poppler Notes: Template idea; fill with your specific constraints. 131. Style pack pipeline for video What it unlocks: Bundle presets/templates so future runs are one flag away. Applied to video. Tools: ffmpeg + ffprobe + ImageMagick Notes: Template idea; fill with your specific constraints. 132. Style pack pipeline for audio What it unlocks: Bundle presets/templates so future runs are one flag away. Applied to audio. Tools: ffmpeg + sox Notes: Template idea; fill with your specific constraints. 133. Style pack pipeline for PDF What it unlocks: Bundle presets/templates so future runs are one flag away. Applied to PDF. Tools: poppler + ImageMagick Notes: Template idea; fill with your specific constraints. 134. Style pack pipeline for SVG What it unlocks: Bundle presets/templates so future runs are one flag away. Applied to SVG. Tools: inkscape + ImageMagick Notes: Template idea; fill with your specific constraints. 135. Style pack pipeline for slides (PPTX) What it unlocks: Bundle presets/templates so future runs are one flag away. Applied to slides (PPTX). Tools: pandoc + poppler Notes: Template idea; fill with your specific constraints. How to use this list with a coding agent 1. Pick an idea. 2. Give the agent: input files + desired output artifact + constraints (duration, resolution, style). 3. Require a dry-run first: print the exact command(s), then run. 4. Add an evaluator: diff image, loudness report, page count, file size, etc. Gemini's ideas Creative & Unusual Tool Workflows Strategy: Generative Media from "Nothing" (Test Sources) Most tools have "test" inputs for debugging. These are actually powerful generative art engines. 1. FFmpeg as a Procedural Video Generator You don't need a camera to make video. FFmpeg has a lavfi (Libavfilter) input device that can generate complex patterns. The Idea: Create "screensaver" style videos using pure math. The Workflow: Use mandelbrot, sierpinski, or life (Game of Life) sources. Command Concept: ffmpeg -f lavfi -i "mandelbrot=s=1920x1080:rate=30" -t 10 output.mp4 (Try exploring the life source for cellular automata visualizations) 2. Audio Synthesis via Math (Bytebeat) The Idea: Generate music using one-line C-style math expressions directly in the terminal. The Workflow: Pipe math from Python or echo directly into an audio player or FFmpeg. Command Concept: ffmpeg -f lavfi -i "aevalsrc=sin(4402PIt):s=44100" -t 5 output.wav (Use complex math like (t5&t>>7)|(t3&t>>10) for chiptune-style glitch music) Strategy: Cross-Domain Data Interpretation (Sonification/Viz) Treating data types as fluid (e.g., "everything is just bytes"). 3. "Hearing" Your Hard Drive (Data Sonification) The Idea: What does the Linux kernel sound like? What does your profile picture sound like? The Workflow: Tell FFmpeg to treat a binary file (like an image or executable) as raw audio data (PCM). Command Concept: ffmpeg -f u8 -ar 44100 -ac 1 -i /bin/ls -t 5 output.wav (Warning: Can be loud/harsh! Results in industrial/noise glitch audio) 4. Visualizing Audio Phase (The "Goniometer") The Idea: Visualize the stereo relationship between left and right channels (classic studio tech, usually expensive software, built-in to FFmpeg). The Workflow: Use the avectorscope filter. Command Concept: ffmpeg -i input.mp3 -filtercomplex "[0:a]avectorscope=s=1920x1080:draw=line" output.mp4 Strategy: The "Pixel-Math" Canvas Using ImageMagick not for converting, but for mathematically programming pixels. 5. Mathematical Art with ImageMagick FX The Idea: Create gradients and patterns by defining the color of every pixel as a mathematical function of its X/Y coordinates. The Workflow: Use the -fx operator. Command Concept: convert -size 500x500 xc:black -fx "sin(i/10)cos(j/10)" output.png (This creates interference patterns based on sine/cosine waves) 6. The "Average" Image (Time Compression) The Idea: Take a 10-second video clip, extract every frame, and "average" them together into a single ghostly image. The Workflow: FFmpeg to extract frames -> ImageMagick to average. Command Concept: 1. ffmpeg -i video.mp4 -vf fps=1 frame%03d.png 2. convert frame.png -evaluate-sequence mean averageframe.png (Great for visualizing "paths" of people walking in a static scene) Strategy: System & Code as Content Using the environment itself as the data source. 7. Git History Video (Code Lapse) The Idea: A video that shows your code typing itself out, commit by commit. The Workflow: 1. Use git log to get commit hashes. 2. Loop through hashes, checkout file, generate image of text (via convert or pandoc). 3. Stitch images into video via FFmpeg. 8. Text-to-Video (Kinetic Typography) The Idea: Flash reading (RSVP) or scrolling text video generated purely from a .txt file. The Workflow: Use FFmpeg's drawtext filter with an expression for the Y-coordinate based on time t. Command Concept: ffmpeg -f lavfi -i color=c=black:s=1280x720 -vf "drawtext=textfile=story.txt:y=h-20t:fontcolor=white:fontsize=24" -t 20 output.mp4 (Creates a Star Wars opening crawl style scroll) Strategy: Glitch & Corruption Intentionally breaking things to create art. 9. Datamoshing (I-Frame Destruction) The Idea: The "melting" video effect seen in music videos. The Workflow: Remove "I-frames" (keyframes) from a video, so the motion of the new scene is applied to the pixels of the old scene. Command Concept: (Requires intricate stream manipulation, often done by converting to .avi and using sed to delete frame headers, then baking back to mp4). 10. Histogram & Waveform Generation The Idea: Create a video that is only the color analysis of another video. The Workflow: Use histogram or waveform filters in FFmpeg. Command Concept: ffmpeg -i input.mp4 -vf "split[a][b];[a]histogram=displaymode=parade:levelsmode=log[hh];[b][hh]overlay" output.mp4 (Overlays the technical color histogram on top of the video) Strategy: Polyglot Files (Steganography) Files that are valid in two formats simultaneously. 11. The Image-Zip Polyglot The Idea: A JPEG image that, when renamed to .zip, contains secret files. The Workflow: Concatenation. Valid JPEGs end with specific bytes; valid Zips start with specific bytes. Most viewers ignore data after the JPEG end marker. Command Concept: cat image.jpg secret.zip > output.jpg (You can view output.jpg normally, but unzip output.jpg also works!)

LLM creative tool capabilities


To solve the junior training bottleneck caused by AI, I stopped hiring beginners to code. Instead, I have them use AI agents to build solutions rapidly, shifting their role to verifying output and designing checks.

Read out by Anand, who is not an AI. See Beating Pangram and AI detectors. These days, AI is reducing the number of entry-level jobs that we have. The trouble is, these are the jobs that are actually training tomorrow's architects. How do we solve this? This is not a new problem. Zoho's Sridhar Vembu posted something that's been bugging me. He said, AI makes senior architects more productive and reduces the need for junior engineers. Then he says, if nobody starts junior, how can anyone become an architect? The data supports his concern. Stanford found that since late 2022, the employment for 22-25 year olds in jobs where AI is strong, like software, fell by as much as 16% compared with older workers who were doing the same jobs. Matt Dean at UCSB also saw this happening in robotic surgery. A phenomenon that happened even before AI came into the picture, because robotic consoles would allow surgeons to do what the residents used to do, and therefore, surgeons stopped bothering to train the residents. But this is not a new problem. Accountants, pilots, and chessmasters have faced this problem and have solved it before in three different ways. For example, spreadsheets made manual ledgers redundant. But manual bookkeeping is how accountants used to learn accounting. That's how they figured out what the different kinds of errors are and how they occur. But after spreadsheets, their job changed. Very few people were checking the arithmetic, and more people were designing the checks and balances that caught the errors. Today there are more accountants than when we were doing manual spreadsheets. In other words, they switched jobs. Autopilots, on the other hand, reduced due junior pilots' flying hours. But when Air France 447 went down, the regulators responded with the FAA 2014 rule that mandates manual flight training. Surgical simulation centers are doing a similar job today. They force professionals to practice those rare cases which automation doesn’t expose them to. In other words, they enforced, since being wrong is dangerous. Chess grandmasters took a different route. Any free phone application today can beat every grandmaster. Chess should have vanished. But instead, chess is now even more popular than it used to be. Chess engines have become the coaches, and the young grandmasters today are much better than those from any previous generation. They upskilled when the journey is more important than the destination. Commercial software is mostly in the switch bucket. Broken deployments and prototypes and quick POCs aren't so important that you can't live with them. You just catch them and move on. So, as a result, I have stopped hiring junior developers to write code. Instead, I hire them to catch the things that AI gets back. One of my interns goes to client meetings, records the calls, feeds the transcripts to an AI coding agent, and builds the solution the client asked for. I've told him deliberately to not even try and understand what the clients say. The clients are experts in their domain, he is not. But, it turns out that he is about three times as fast as anyone else with five years of experience, because that experience is the bottleneck. Because the experienced people are trying to understand things and slowing the system down. For mission-critical software, this is dangerous. Wrong code in a trading system or a medical device can hurt people. In such cases, it's important to build coding as a skill deliberately. Using AI as a simulator or as a coach can be really powerful, because Bainbridge's irony of automation still applies. "The better the machine gets, the rarer the human intervention, and the harder it is to stay sharp for the one time it matters." Which bucket your software is in may not be obvious upfront. If we get it wrong either way, it costs us money or harm. Either we overtrain, or we underenforce. Vembu is not sure how to resolve this. Nor am I.

No Juniors, No Experts


Traditional junior developer tasks are disappearing. To adapt, I hire for how well candidates review and direct AI agents like Claude Code, rather than raw coding, while using AI as a simulation tool for high-risk training.

Generated by ChatGPT. See Beating Pangram and AI detectors. Ankor runs a company of several thousand people. After a bunch of calls with one of our interns, Varun, he messaged me: "This guy is fantastic. How is he doing it?" This is what Varun was doing: he recorded calls, fed the transcript to Claude Code or Codex, and delivered results. That's nearly the whole process. He didn't interpret the content. He didn't apply much domain knowledge. He got out of the way. I had told him this deliberately: "Ankor will say something. Don't try to understand it. You will not understand it anyway. Record the call. Transcribe it. Give it to Claude Code. Deploy to GitHub. Show Ankor. Take feedback. Repeat." Varun was thrice as fast as people with five years of experience. Weirdly, the experience was the bottleneck. This is the part I like. It is also the part that makes me nervous. Sridhar Vembu recently asked, roughly: if AI makes senior architects more productive but removes junior work, how does someone become a software architect without first being a junior engineer? Fair. My first answer was: maybe juniors should stop doing what AI already does well. My second answer was: wait, that sounds dangerous. My third answer, which is where I am now, is: what juniors should learn depends on what it costs to be wrong. For most software, wrong is cheap. A bad dashboard. A broken prototype. A weak first draft. An internal tool that falls over. A marketing email that sounds like it was raised entirely on LinkedIn. Annoying, but usually recoverable. In such cases, I don't see much point in preserving the old junior task out of affection. If AI writes the CRUD app, fine. Let it. The junior should learn what happens around the CRUD app: choosing the problem, giving context, reviewing output, spotting nonsense, asking for changes, deciding what is safe enough. That is why my hiring question has changed. I no longer ask only, "Can you write code?" I increasingly ask: "Can you stop slowing down AI?" This is an odd hiring question. I don't know if I like it. But it predicts usefulness better than the old ones, at least for the work I do. The old signals are breaking anyway. I teach a data science course at IIT Madras. In March 2026, I pointed a coding agent at one of my own exams. It had 22 questions and was meant for 45 minutes. The agent solved everything well within time. The highest score any actual student got was 50 percent. Second highest: 33 percent. And I no longer had a clue what "hard" meant. That was not a student crisis. It was a measurement crisis. My instruments were calibrated for a world where people produced the output directly. That world is becoming... less available. So before releasing questions now, I copy-paste them into ChatGPT. If it answers, I revise the question. I am using AI to invalidate my own exam instruments in real time. Strange sentence. Still true. Companies have the same problem with interviews. If candidates use AI secretly, the test becomes an honesty test. Actually, maybe worse. It rewards people who use AI and hide it well. That is not the skill I want. What seems to work better is: give someone a vague problem, an AI coding agent, and a few hours. See what useful thing comes out. Then ask what the agent got wrong. The output alone does not prove much now. The review process tells me more. But this applies only where wrong is cheap. Some work is different. A wrong drug dose. A wrong trade. A bridge. An airplane. Security code. Medical software. Payment systems. Anything where the blast radius is bigger than "oops, redeploy." There, I would not say "just get out of the way." Automation has an old irony. The better the machine gets, the less practice humans get, and the more helpless they are when the machine fails. Robotic surgery saw this before LLMs. Senior surgeons could do more through robotic consoles. Great. But residents lost the messy hands-on work through which they learned. Efficiency quietly ate apprenticeship. Pilots had a similar problem with autopilot. So aviation did not say, "Nobody needs to fly manually anymore." It added simulator time and manual flying requirements. Maybe software needs more of that. Not for everything. Please don't make every React intern attend Kubernetes Incident Simulator Camp. They will leave, and they should. But for high-risk systems, AI should become the simulator, not the excuse. Make it generate rare failures. Make it write evil test cases. Make it role-play the bad customer, the regulator, the attacker, the tired reviewer at 2 a.m. Make juniors practice judgment when the system is trying to fool them. Then there is the third bucket: work we do because we like doing it. Chess engines can beat any human. People still play chess. In fact, chess got stronger because engines became coaches. Some coding is like that too. I still code for the joy of making something exist. Often badly. Often at night. Often instead of sleeping, which is a separate governance problem. So will AI replace junior techies? It will replace many junior tasks. It already has. But maybe "junior engineer" was never just a bundle of tasks. Maybe it was a protected way to practice. If so, companies should protect the practice, not necessarily the old tasks. I am not fully sure what the new apprenticeship looks like. Right now, mine looks like this: record the call, give it to the agent, show the result, take feedback, repeat. Then, slowly, notice what the agent cannot do. Maybe that is where the next architect begins.

No Juniors, No Experts


I examine how AI is replacing junior developers and offer three frameworks—Switch, Enforce, and Level-up—to train the next generation of software architects based on your system's tolerance for error.

Generated by Claude. See Beating Pangram and AI detectors. AI is cutting the entry-level jobs that used to train tomorrow's architects. Aviation, chess and bookkeeping have run this experiment before, and solved it three different ways. Zoho's Sridhar Vembu posted something that's been bugging me: AI makes senior architects more productive and cuts the need for junior engineers. Then the harder line: if nobody starts junior, how does anyone become an architect? The data backs his worry. Stanford found that since late 2022, employment for 22-to-25-year-olds in AI-exposed jobs like software fell 16 percent relative to older workers in the same roles. Matt Beane at UCSB watched this happen in robotic surgery before AI arrived: robotic consoles let surgeons do what residents used to do, so surgeons stopped bothering to train residents. I don't have a clean answer. But history has three, and which one applies depends on what happens when the entry-level worker gets it wrong. Switch, when being wrong is cheap. Spreadsheets made manual ledgers redundant. But manual bookkeeping used to teach accountants how errors happen. So the job changed: fewer people checking arithmetic, more people designing the checks that catch it. There are more accountants today than before spreadsheets existed. Enforce, when being wrong is expensive. Autopilot cut junior pilots' hand-flying hours until Air France 447 went down. Regulators responded with the FAA's 2014 rule mandating manual-flight training. Surgical simulation centers do the same job now: they force the rare-case practice that robotic consoles took away. Level-up, when the work is the point. A free phone app now beats any grandmaster. Chess should be dead. Instead, engines became coaches, and today's young grandmasters are stronger than any generation before them. [Suggested visual: three-panel strip - cockpit dash, chess board, ledger/spreadsheet - captioned "Switch, Enforce, Level-up"] Most commercial software sits in the switch bucket. A broken deployment, a weak first draft: you catch it and move on. So I've stopped hiring junior developers to write code. I hire them to catch what AI gets wrong. One of my interns records client calls, feeds the transcript to a coding agent, and ships. I told him deliberately not to try to understand the domain. He's three times faster than someone with five years of experience, because experience was the bottleneck. For mission-critical software, this doesn't hold. Wrong code in a trading system or a medical device sits in the enforce bucket: build the skill on purpose, using AI as the simulator, because Bainbridge's old irony of automation still applies. "The better the machine gets, the rarer the human intervention, and the harder it is to stay sharp for the one time it matters." Which bucket your junior engineers are actually in isn't obvious. Get it wrong either way and it costs you: over-train for switch work and you waste everyone's time; under-train for enforce work and you're one Air France 447 away from finding out. Vembu is still thinking through how this resolves. So am I.

No Juniors, No Experts


Things people have shared about my Tools in Data Science course

20 May 2026 Suhani01 I received a mail mentioning, “If you have already completed the course in the past 1 year, we encourage you to share your feedback about your experiences and what worked for you in TDS in the same Discourse thread.” So, here goes: I had taken TDS in May 2025 term ad I did not know it would be so difficult, because I had not read the guidelines before selecting it. And by the time I read the guidelines, I had already paid the registration fee. 🥲 Although I ended up with ‘C’ grade, this was the most enjoyable and unpredictable course out of all diploma courses. A lot of students might disagree with me calling this course ‘enjoyable’, but this is the only course which keeps you on your toes and challenges you every single day. You can make the maximum number of friends in TDS, because this course is not about being intelligent. It’s about the skill of ‘jugaad’ (being resourceful and smart enough to work around problems, not necessarily solve them). TDS teaches you stuff which you can never get out of conventional textbooks, like figuring out what resources to use, how to read material selectively, and how to use the system to beat the system. Most importantly, TDS teaches how to deal with real-life corporate and industry scenarios, which are also as unpredictable, and have no defined rules or syllabus. You’ll never get a textbook or steps to follow, you will have to read the documentation, watch YouTube videos, and discuss with friends to get to the solution yourself. Moreover, the satisfaction of completing a GA after hours of effort is unmatched! 😃 Most importantly, TDS has taught me consistency and resourcefulness, and given me a weird sense of confidence. Now whenever I get something difficult, like an undoable project or assignment, I just think that if I can complete TDS, then there’s practically nothing that I can’t do 😁! Also, if the course is difficult, then the course team is also very supportive and patient. They would take additional hours of live lectures just to clear the most basic doubts and explain everything all over again from scratch. TDS has the most patient and approachable professors and instructors. And I am saying that as a dual degree student who has completed almost all diploma courses. @carlton sir was patient and calm enough to solve every single student’s query, however time-taking it was. Even Anand sir took a few of our live classes. And the TAs were also very helpful, explaining every concept from the basics. I’m not sure if the TAs are the same right now, but during our term, there was Hritik sir and Jivraj sir. I will always be extremely grateful to them. Ultimately, getting a good grade in TDS is up to you. While some students failed, a few even got a perfect 100. You’ll have to give it a lot of time and consistent efforts. TDS alone takes as much time as all the rest of the courses combined. Even after that, you can never be fully prepared. There will always be a surprise waiting for you (like getting the ROE in German instead of English, which happened in our term 😂 and we ended up wasting 5-10 minutes because of the shock)! Finally, this long message was not to put anyone off or demotivate anyone from taking TDS, but to take the challenge head-on, and utilise it as your greatest learning opportunity. All the best 👻 Enjoy!!! 30 Aug 2023 s.anand: @ankit.jain – I’m the culprit behind this RoE structure. Thanks for the opportunity to share my thought process. What does this RoE evaluate? Implicit learning. Implicit learning is “How much can they answer if woken up from sleep?” Explicit learning is “How much can they answer given time and Internet?” Some may know 10% implicitly. Some know 50%. They’ll answer those in a few seconds. Some, they can FIND out. with Google, StackOverflow, ChatGPT. That’s explicit learning. But it takes time. Some, they just CAN’T find out. Maybe the terminology is unclear. Maybe their skill set is different. The RoE evaluates how much of learning is implicit. (Projects test how much is explicit.) Can you answer 17 Q in 30 m? Hopefully not. I hope this is at the edge of the class’ competence. If multiple people answer all 17, I’ll suggest 20 Q in 30 m next time, or pick tougher questions. (This sounds harsh. Over time, though, I’ve come to value frank feedback over polite encouragement.) What knowledge helps solve it this fast? Practice. 3 strategies help. 1. Consistent practice. Practice regularly. Pick problems just outside the edge of competence (fail 50% of the time). 2. Social learning. Observe experts & peers and internalize their strategies. We’re social animals and learn faster through mimicry. 3. Emotional engagement. If we like it or enjoy it, we learn faster. Practicing on real-world problems or problems we enjoy solving, working with people we enjoy, helps. Is it worth it? Maybe not. Not all implicit learning is worth it. 1. You may not need it. 10 years ago, as a data scientist, scraping was worth learning implicitly. Today, as a manager, I’d just hire someone to do it. 2. You may not be good at it. When I got a “D” in German, followed by a “D” in Japanese, I realized I’m just not mentally wired for human languages. It’d be too much effort to learn. The RoE scores will give an idea of your implicit learning. But your time is limited. Implicit learning is costly. Please focus your time judiciously.

TDS Feedback


I detailed my 1999 Aditya Birla scholarship interview experience at IIM Bangalore. I found the selection process focused on resume points and write-ups, while the star-studded panel asked about Chaos Theory, character, and social impact.

First year students ranking in the top 20 in CAT from each of the IIMs are eligible to apply to this scholarship. It pays for the tuition fee for the two years at IIM-B, and hence is worth about Rs. 2 lakhs. The resume is the key to shortlisting. The Aditya Birla group assigned a weightage to each achievement (depending on whether it was at the national level, state level, college level, etc.) and added up the points. The top point scorers were chosen. Some points are awarded to the write-up also. From IIM-B, Vijayalakshmi and myself were shortlisted in 1999. 8 were shortlisted from IIM-A and IIM-C respectively, while 2 more were from IIM-L. The scholarship was awarded to 10 people finally. The distribution was 4-1-4-1 across A, B, C and L. Viji won it from IIM-B. In 2000, 13 were shortlisted from IIM-B, and the following 8 were in the 10 that won the scholarship. Vikas Purohit, Karan Bajaj, Prahlad Rao, Yashodhara Lal, Pratyush Tiwari, Lavanya Chari, Prashant Koorse, Saurabh Jhalaria In 1999, Viji & I were put up at the Grand Hotel. They briefed us the earlier night about allowances (Rs. 1,000 + 50% of the travel fare). Since I'd flown, I ended up making a loss on the trip -- but spending an hour at the Taj Hotel was worth it. The interview was spread across the next day from 9AM to 6PM, and the results were announced over dinner at 8PM. We flew back the next morning, just in time for Prof. Ramesh Kumar's first lecture on marketing. The interview panel was 'star-studded'. I didn't know anyone except Dr. Alagh of the planning commission. The others were from NGOs and big companies. Interview questions 1. Which is more important: character, competence or charisma? 2. What do you think India needs to do to improve? 3. How do you plan to contribute socially after you graduate? 4. How can an educational institution like IIM-B take steps to improve its effectiveness? 5. Tell us about some challenges that you faced when at work. It was an ad-hoc interview, only partly based on the resume. The only question based on the resume was "How will you apply Chaos Theory to management?" Mine was the first interview, and I thought I had done well. Learnings 1. The writeup is critical. They hired an external agency to do the evaluation, and study it very carefully. 2. The competition is the toughest I have faced. Guys from the other IIMs (they were all GUYS, except Viji) are extremely smart. 3. I think the interview counted for more than the writeup, at least after the shortlist. I had done fairly well in the writeup, and the interview was the unknown factor. Comments gurdeep singh 20 Nov 2008 12:48 am: I am gurdeep singh from bangalore . am 1st year MBA student.. i want to know that can i apply for schlorship? please help me regarding this. S Anand 20 Nov 2008 1:58 am: @Gurdeep: If you're in your first year at IIM, the scholarship details will\ be announced to you. To my knowledge, the scholarship isn't available\ outside of the IITs and IIMs. Aiborlang Andrew Chyne 6 Oct 1999 12:00 pm: Can I get an educational sponsorships from the top MNC's. Pushp Saurav 29 Sep 2008 10:23 am: Anand,\ I, a 3rd year student of BITS-Pilani, am a Aditya Birla Scholar of 2006 Batch. Had gone to attend the 10th anniversary of ABS, held in The Taj, Mumbai. A scholar from your batch Prashant Sarin had also come to attend this ceremony. Do you know him ??? Anonymous 25 Nov 2010 8:21 am: uhm..i got 431 this year, dats in JEE-2010 Anonymous 25 Nov 2010 8:20 am: uhmm...actually m a 1st yr undergraduate student iit kharagpur and had secured an AIR 431 which lies int he top 15 ranks of my college. i was never told of this scholarship nor any announcements ver made in dis regard. i seriously regret not having applied for this scholarship..it was today i learnt that i cud hv been eligible.. is der nething i can do now? i kw its kinda late... vibhor jain 1 Oct 2011 8:20 am: I want to ask why is this scholorship is not given for other eligible students of other colleges many hundreds of colleges are there and this is not necessary that entire talent of country is in iit's or iim's these insitutions are not running up the whole country so what about the other non priviledged deserving students???? further these iims and iits have so much variatiion in admissions due to quota etc? so what about other thousands of youngsters they are also indians and they also have right on resources and wealth of country if they are eligible so i think "ADITYA BIRLA SCOLORSHIPS SHOULD BE OPEN FOR ALL COLLEGE STUDENTS OF INDIA"

Aditya Birla scholarship interview


I built a script to track user login times while exploring CGI. I'm using the CGI.pm Perl module to handle web forms and generate HTML, making server-side web development significantly more manageable.

I was playing around with CGI and wrote a script to determine when somebody last logged in. Read about CGI.pm.

CGI.pm


I prepared for the Citibank Leadership award interview at IIM Bangalore while recovering from a fractured ankle. I found they prioritized well-rounded personalities, weighing personal experiences and communication skills heavily based on my written application and resume.

Citibank awards Rs. 50,000 to 2-3 candidates from IIM Bangalore based on leadership traits. We had to submit 'brief' writeups on what leardership is, why we're good leaders, what our social contributions and academic achievements are, etc., along with our resume. We also had to turn in a student and faculty nomination. Since I had lots of time (I was bedridden with a fractured ankle) I prepared quite well for this interview. 11 were shortlisted. The interviews were scheduled for 20 minutes each. My preparation largely involved reading what I'd submitted, and preparing for some standard questions like 'What are your career goals?', 'Strengths/Weaknesses', etc. In our previous batch, 3 people won the award -- Hemalata, Saurabh Singh and Sahil Bhandari. All 3 were good speakers with accents. So I brushed up my accent too -- turned out to be unnecessary, though. Prof. Umesh Rajamani & Prof. Rupa Chanda were on my panel. They asked me about my leg (I was on crutches), and went on reading the writeup. All questions were directly based on the writeup. Interview 1. Who do you think are easier to lead? Tamilians or Kannadigas? (Prof. Umesh Rajamani asked this question, and soon said that he wasn't really looking for an answer.) 2. Tell me about your experiences as a project leader at IBM. 3. Some details on your social contributions... (based on the writeup) 4. What are your extracurriculars at IIM-B? 5. What did you learn as the captain of your basketball team? Mostly, they were asking me to expand on what was there in the writeup. It was a relaxed atmosphere, and Prof. Rupa Chanda was very encouraging. The results were announced on 3rd March. Sunny Sharma and I made it. Learnings 1. I think they were looking for a well-rounded personality. 2. Personal experiences were given a lot of weight. They were especially interested in what I had done in such-and-such a situation. 3. all questions were based on the writeup and resume. I feel they gave equal weightage to the interivew and the writeup -- but the writeup may have been used only for shortlisting. 4. Confidence during the interview was very important. 5. They were looking for someone with the ability to communicate well, too. Comments abhishek 10 Nov 1999 12:00 pm: it is great help to students like us to put such a interview in the site T.R.Kiran Kumar 29 Oct 2008 11:34 pm: All question were related on one point to know Personality & his Patiency.\ How far he can manage Risk analysis\ & How confident his answers was. (Pratically & Proffessionally) Roshan L. Joseph 10 Mar 2013 7:41 am: Please give me Prof. Umesh Rajamani's email id as I am a friend of his father and wish to contact his Dad

Citibank Leadership interview


I took the Keirsey temperament sorter, an online Myers-Briggs test, and discovered I'm an ENTP. I share this personality type with figures like Walt Disney, Richard Feynman, and Calvin from Calvin and Hobbes.

The Keirsey temperament sorter is an online Myers-Briggs test. My type is ENTP, which I share with Walt Disney, Richard Feynman, Steve Jobs and Calvin (of Calvin and Hobbes.) Comments Thejesh GN 14 May 2009 8:13 am: Good good. This is almost 10 year old. You started blogging long back! The Calvin and Hobbes search Takedown | s-anand.net 21 May 2010 11:53 am (pingback): [...] when I started reading Calvin & Hobbes. The earliest reference I can find in my blogs is in July 1999. I remember it didn’t take me long to become a fan. I’d read every strip on the newspaper; hunt [...]

Keirsey temperament sorter


I reflect on my 1999 Lehman Brothers interview for Sales, Trading & Research, detailing how my IIT background and minimal preparation led to a Tokyo placement. I share tips on resume shortlisting, mock interviews, and tech stock valuation.

Lehman Brothers was recruiting Sales, Trading & Research in Tokyo, and Investment Banking in New York. If that sounds like greek, read Vault's report on investment banking. They seemed disappointed at the number of questions that came their way during their pre-placement presentation. There were hoping for a lot more, and agressive, questions. The people who came included Alan Cutter, Pamella, Isabella, Sarab Bhutani (all from New York), Dalip Awasthi and Sumant Gupta. They shortlisted 21 people for New York and 9 people for Tokyo. Rajesh Dalmia and I were on both shortlists. My preparation for the interview was minimal. I went through the day's newspapers; found out Lehman's and IBM's stock price (IBM because I used to work there); the Sensex, NASDAQ, Nikkei, etc. Read an article in the Economist on Central Banks (Sept '99). Overall, I put in about 3 hours on the previous day. The first interview was with Dalip and Sumant. They had split themselves into 3 panels. Dalip and Sumant were for STR, while the others interviewed the remaining candidates. Sumant's opening question was, "So you were at IIT Madras?" He was from IITM too. A year senior to me. I said, "Yeah. You were at Jamuna Hostel, right?" We went on a bit about IITM after that. Interview What were you doing at IBM? (We went into quite a bit of detail.) What are your hobbies? (Again, quite a bit of detail.) How do you value technology stocks? (This is where I scored. I said nobody knows.) How did you find Japan in your earlier visits? Sumant advised me to speak a little slower, and sent me to the next panel. Isabella and Sarab asked me about my long term plans, my intentions to work abroad, and whether I preferred I-Banking or STR. I said, "Equity research looks the most attractive, based on what I hear." After a while, Sumand and Dalip called me back and asked a bit about basketball. With that, the STR interviews were closed. By 11PM, they announced that Manoj would be going to New York, and I would be working in Tokyo. Learnings The resume matters a lot. I filled mine with what looks 'impressive', and was shortlisted for both I-Banking and STR. Lehman's shortlisting parameters are: a good academic record, work experience in a reputed firm, and extra-curriculars -- strictly in that order. It helps to have a senior in the panel. (Manoj is from the IITs too.) I think my work experience and prior travel to Japan worked in my favour too. If I were preparing again for the Lehman Brothers summer interview, here's how I'd go about it. First, get a thin book about how to crack an interview from the library and read it, end-to-end. I say thin because it's not worth spending more than 2-3 hours on the book, and you DO need to read it end-to-end. Of course, guides are available on the Internet, but it would be cheaper to borrow it than print it out. Second, know thyself. That's the most important part. Here are some questions for which you should have ready-made answers for. The rule-of-thumb, of course, is to be perfectly frank. Why do you want to join Lehman Brothers / Investment banking / Finance? What other companies have you applied for? How have you been doing at IIM-B? Tell me more about (any item on your resume). What did you like/dislike about (any item on your resume). What are your strengths and weaknesses (3 of each)? Where do you see yourself 5/10/20 years down the line? Ideally, you should get someone to interview you, ask you some of these questions. Catch your classmates, your seniors, anyone. Ask them to give you feedback on their first impression of you, and whether, if they were in that company, they would hire you. More importantly, why they wouldn't, if at all. Third, find out what the recruiters would be looking for. My guess is, they're looking for someone with Good communication skills -- so speak slowly and clearly. Confidence -- so think your answer before speaking; ask for time if you need to think; relax if you've made a mistake. Analytical skills and intelligence -- so say "I don't know" when you don't, and tell them about all the analytical and intelligent things you've done before. Fourth, learn a bit about the industry. Vault and Wetfeet have good industry guides. Don't read it end-to-end. Just skim through it and get a feel of things. People haven't gotten a feel of it after 2 months of working there, so perhaps 2 hours of skimming won't tell you much. But it'll get you used to the kind of words that are used there, like "80 hours a week", "bond price", etc. Fifth, learn some concepts. You need to know what a stock or a share is, and what a bond is.f you've worked, you may like to know the share price of your former company, and why it's there. You probably ought to have an opinion on some of the things happening in the business arena, so if you don't have one, get one. Also make sure to look through SEO reseller pricing to pick out the best marketing strategy for your company. I've listed some possible questions below, and my answers, had I been asked these. Do you think dot-coms are overvalued?: Yes. I don't think that the productivity growth will benefit companies selling computers. I think it will benefit the users of computers. (No one knows, really, but we need an opinion and a reason.) Are the second-phase of reforms going in the right direction?: No idea. Why is the Euro falling, or why is the dollar rising?: No idea. How would you value a petroleum company?: (I'm a chemical engineer, but...) I don't know. Well, the point, I guess, is not to have answers to all questions. The answer is to have a reason for any answer that you give. So do find out about what's happening in the world. Read the papers. But don't bother remembering everything. Just have an opinion on a few items of importance, with a reason. Best of luck! Comments vishal 20 May 2007 7:13 am: I think this would really help ..its given nicely..& i have even copied it.. thanks for posting nikhil 9 Oct 1999 12:00 pm: Hi,thanx for ur guidance .... vikrant 9 Oct 1999 12:00 pm: thanks buddy ... great use Sera 9 Oct 1999 12:00 pm: I m thinking of applying for an entry level analyst position at Lehman Brothers in Japan. Your tips gave me a very insightful idea about how I should preapre for my interview. (hopefully i'll make it to the interview.) thanks for the posting!

Lehman Brothers interview


I shared the US District Court's findings ruling Microsoft a monopoly. I found the document to be a fascinating economic analysis of the company's market power and its impact on the software industry during the late nineties.

Microsoft has been ruled a monopoly. The findings are a pretty interesting economic analysis. (The US District court site also has a copy.)

Microsoft is a monopoly


I observed an early Google bomb where searching "more evil than Satan himself" returned Microsoft’s homepage. I tracked the result’s disappearance and reappearance in 2000, highlighting early volatility and manipulation of search engine rankings.

Curious that Google should return Microsoft's home page when you search for "more evil than Satan himself"... When I tried this on 24th June 2000, it didn't work. Maybe Google got smart. Or was it Microsoft? On 3rd July 2000, it worked again. Comments Anonymous 18 Dec 2006 3:11 am: I tried it, doesn't work now Max 30 Mar 2009 6:26 pm: It's been fixed, Microsoft (and also Bush) were pretty mad at Google.

More evil than Satan himself


I emphasize why punctuation is vital for professional communication. Glaring errors can change a sentence's meaning or make you look careless. Proper usage ensures your writing remains clear, effective, and free from embarrassing or confusing mistakes.

Punctuation is critical. Believe me, mistakes can be glaring!

Punctuation is critical


I detail my IIM Bangalore exchange interview experience, where I secured a spot at London Business School. I focus on navigating cultural questions and the importance of having prepared, passionate answers regarding social impact and university contribution.

There were 22 vacancies, and 45 were shortlisted (out of less than 70 applicants). We were interviewed by 5 panels, each with 2 professors. We had submitted our resumes, a writeup on why we were applying for the programme, various declarations and our grade sheet. Though it was rumoured that grades played a 50% part in shortlisting, it was not so. Each panel ranked their candidates independently (in which grades played only an implicit part) -- so it was the interview that really counted. After ranking, they pooled the rankings across panels (this is probably where grades might come in) and allocated the first available preference by rank. If the universities you opted for are not available, you would not be considered for other universities even if your ranking is high. So it makes sense to fill out all the universities of your choice if you're keen on going. One standard question acroess panels was on aspects of Indian culture -- particularly in Prof. CM Reddy's panel. Questions ranged from "What was the Yaksha's last question to Yudhisthira?" to "What is the essence of Indian spiritual philosophy?" Other standard questions were "What will you do for IIM-B once you come back?" and "How will you serve as the ambassador of IIM-B?" Interview 1. How did you break your leg? 2. Do you think businesses have a social function? 3. What will you do for IIM-B when you come back? 4. Tell me more about your social contributions. (From my resume.) 5. What is the central message of Indian philosophy? Prof. Mahadevan and Prof. Prakhya interviewed me. Both were IITians, and I discovered that Prof. Prakhya was also my school senior. Prof. Mahadevan was genuinely seeking an answer to all his questions. That is, he was really interested in how exchange students could improve IIM-B's functioning. Prof. Prakhya was pretty sharp, and tried pricking holes in my arguments. Before I left, Prof. Mahadevan commented, "This is nothing to do with the interview, but I just wanted to say that, based on your resume, you have a great future." Pallavi and I were selected for London Business School. Learnings 1. I had ready-made answers to all their questions, and that helped. 2. I was passionate about all the answers. I think a feeling of genuineness came through. 3. As always, the resume counted for a lot. Comments Ramya 18 May 2007 8:15 am: Can I ask you to guide me thru the interview processes in Insead.In addition to this , they also have asked me to sumbit a brief yet all inspiring essay to avail the scholarship that can help me negate atleast 25% of the course fee..Thanks - Ramya Gopinath 31 May 2011 7:06 am:Hi Anand,Just to trace back, can you just post as to what answers you gave to these questions. Gopi

Student Exchange Interview


Explore the Web Developer's Virtual Library to access comprehensive web design guidelines and technical tutorials. This historic resource offers foundational best practices and standards essential for building and maintaining functional, well-designed websites.

Web design guidelines are available at the Web Developer's Virtual Library.

Web Developers Virtual Library


I practiced case interviews with the consulting club at London Business School and attended lectures on the US economy by Andrew Scott and Nick Craft. I also noted the school's newly renovated lecture theatres and unique presentation styles.

Well, apparantly LBS has just had its lecture theatres (LTs) newly made! Which is why they look so good, I hear. At least, the Professors keep commenting about how new the LTs are, and how they're unused to it and all that. This afternoon, Pallavi, another exchange student, an MBA 2001 student and myself, got together and ran a series of mock interviews. LBS' consulting club has some very good material on case interviews. Today we had a lecture on 'World Economy: Problems and Prospects'. Professor Andrew Scott was awfully funny. We discussed the reason for the growth of the US Economy today. Well, we're still not too sure why it grew, but IT may be part of the reason. Following the lecture, Nick Craft, a guest lecturer from the London School of Economics, came and gave an interesting talk on the same. Bit of a problem with his slides, though. Self-admittedly, he failed arts in school, and his combination of a bright green gradient against a purple background can leave no stomach unturned. Looks like this course is going to have guest lecturers in each class, and they all look like big shots.

A day at LBS


I documented an exhausting day at London Business School involving Diwali planning, consulting presentations from Booz-Allen and AT Kearney, a nasty lunch mishap, and falling asleep during guest lectures before a late-night finish.

A rather tiring day. 09:00 am: Wake up, and still feel sleepy. 10:00 am: Leave for LBS 11:00 am: Reach LBS. Check mails. These days, it takes a couple of hours. 12:30 pm: Attend India Club meeting for Diwali celebrations. Very well organized. 01:15 pm: Presentation by Booz-Allen & Hamilton. Pretty good. Manage to stay awake. 02:15 pm: Eat lunch. Stupidly eat prawns without seeing the labels. Almost vomit. 03:00 pm: Group meeting. Discuss Dell. 04:15 pm: Fall asleep in AT Kearney's presentation. 05:15 pm: Stay away from anything that looks non-veg during tea. 06:00 pm: World economy class. Excellent professor. Terribly funny. Everything makes sense. 07:00 pm: Guest lecturer. Fall asleep. 08:00 pm: Back to Prof. Scott. Wake up and listen. 09:00 pm: Answer more mails. 10:00 pm: Chucked out of computer center. Go home. 11:15 pm: Have dinner. midnight: Crash.

A tiring day


I recommend exploring AdFlip, a digital archive of famous print advertisements. It is an excellent resource for analyzing historical marketing trends, graphic design evolution, and iconic brand campaigns from past decades of print media.

AdFlip is an archive of famous print advertisements.

AdFlip


I'm skeptical of AdReady’s concept to trigger pop-up ads near the cursor when the mouse is idle. While it's a novel mechanism, it would interrupt my reading and seems far too easy for competitors to replicate.

AdReady has a neat idea: pop up advertisements near the mouse pointer, when the mouse is sitting idle. Cool. But I don't want anything popping up when I'm reading! Besides, since this is an easy idea to copy, I doubt they should have it as their USP.

Ads when idle


I found Advanced Stock Information to be a helpful resource for its curated collections of top-10 financial websites. It organizes the best tools for stock analysis and investment research into easy-to-navigate categories.

Advanced Stock Information has a nice set of collections of the top-10 financial sites in various categories.

Advanced stock information


I balanced home-cooked vatha kozhambu with a day at LBS, where I felt like the slowest typist in the lab. I also navigated multicultural group projects and attended a stylish, insightful recruitment presentation by BCG.

We made some vatha kozhambu at home this morning. Now, you'll have to take my word for it, because we ourselves weren't very convinced. But it was hot. It was thick. And though it had too much tamarind, it tasted great (or so we say). After that heavy bruch, it was time for LBS. I think I'm the slowest typist at LBS. The speed at which the keyboards chatter around me is incredible. So fast, in fact, that I lose my nerve and tend to make mistakes or type slowly. The guy to my right, for example, is glued to the monitor and is typing about 3 characters for every keystroke of mine. So far, he hasn't pressed backspace. Luckily, the lady to my left is using the mouse more than the keyboard! We had the second group meeting of our 'Dynamics of Strategy' group yesterday. The group has 2 Indians, 2 Germans and a Mexican. The first meeting of our 'Mergers & MBOs' course was today, and that group has 1 Indian, 1 German and 1 Japanese. Actually, the accent is the least of the problems. It's getting to figure out a way of working that's the real hurdle. But the good part is, everyone's focused, willing to take initiative, and follow guidelines. No problems so far. BCG gave their presentation today. Extremely impressive. About 3 managers, 2 partners and 5 consultants came for the presentation. 2 of them presented, and the presentation was entirely about the life of a consultant. Not the technical life -- no. It was largely insights into the social life. They explained why they came to consulting, how they felt the thrill in consulting, how they balanced their family life, had to make compromises, etc. It seemed very balanced. The best part was a video which involved BCG's clients, family members of BCG consultants, and ex-BCG employees, but no BCG employees at all. That proved an excellent way of telling us what it's really about. I'll hand it to BCG for doing things in style.

Another day at LBS


I'm documenting ongoing interactions between unsuspecting AOL users and AOLiza, a simple chatbot. These transcripts, like a desperate conversation with a Starbucks employee, capture the strange and often poignant ways people open up to automated programs.

AOLiza continues. People still have conversations with a program in a chat room, without knowing it. Conversation 42, for example, is a fairly desperate 23-year old working in Starbucks, and...

AOLiza conversations


After visiting the Louvre and questioning the hype surrounding the Mona Lisa, I've decided to explore more art and culture. I started with the Van Gogh light exhibition to gain a better appreciation for famous works.

Not that I'm into art or anything, but ever since I saw the Louvre, and came out wondering what's so great about the Mona Lisa, I figured I may as well get some culture. The Van Gogh light exhibition is a good start.

Appreciating art


I found Apps.com, an organized directory dedicated to Internet applications. It serves as a useful central hub for finding and categorizing various web-based software and online tools during the early growth of the web.

Apps.com is a directory of Internet applications.

Apps.com


I revisited Astalavista, an enduring underground search engine specializing in security and hacking resources. Its longevity suggests it remains a reliable tool for those seeking specialized technical information outside mainstream search platforms.

AstaLaVista is an 'underground search engine'. I'd been there before, and since its survived this long, it must be good.

Astalavista


StrongNumbers identifies the fair market price of products by searching through historical auction data. Use it to find accurate transaction values and real-time market information before buying or selling items online.

Strong numbers searches through auctions and tells you what the fair price of any product is. Now, that's market information!

Auction prices