Special topics in Kernels, RL, Reward Hacking in Agents
Conference Context
- Date/time: 2026-06-29 · 2:20pm-5:30pm
- Track/room: Workshops Day 1 · Track 3
- Speaker(s): Daniel Han
- Session type/status: session · confirmed
- Track: Workshops Day 1
- Room: Track 3
- Session type: session
- Status: confirmed
Session Description
An advanced seminar (good prerequisites: Daniel's 2024 and 2025 hit AIE workshops, but all are welcome!) PLS WATCH: https://www.youtube.com/@aiDotEngineer/search?query=daniel%20han
Media Evidence
(Full Workshop) Reinforcement Learning, Kernels, Reasoning, Quantization & Agents — Daniel Han (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions).
- Source video:
youtube-OkEGJ5G3foU - Slide deck: [[youtube-OkEGJ5G3foU-dense-slides|Dense Slides: [Full Workshop] Reinforcement Learning, Kernels, Reasoning, Quantization & Agents — Daniel Han]] — no readable content slides after AI classification.
- Additional slide evidence: [[youtube-OkEGJ5G3foU-slides|Slides: [Full Workshop] Reinforcement Learning, Kernels, Reasoning, Quantization & Agents — Daniel Han]], [[youtube-OkEGJ5G3foU-reconstructed-slides|Reconstructed Slides: [Full Workshop] Reinforcement Learning, Kernels, Reasoning, Quantization & Agents — Daniel Han]]
- Slide-derived themes for
youtube-OkEGJ5G3foU: fixes, chat, template, multiple, llama, research, google, github.
Evidence Graph
This evidence graph is generated from currently linked source material: official schedule text, related video pages, cached transcripts, visible slide text, dense/reconstructed slide pages, and AI slide-classification audits.
Media Signals
youtube-OkEGJ5G3foU— 3 slide-derived text signals- Slide-derived themes for
youtube-OkEGJ5G3foU: fixes, chat, template, multiple, llama, research, google, github. - Evidence links for
youtube-OkEGJ5G3foU: youtube OkEGJ5G3foU, youtube OkEGJ5G3foU slides, youtube OkEGJ5G3foU dense slides, youtube OkEGJ5G3foU reconstructed slides
Agent Reading Notes
Use these signals to refine the synopsis, topic links, people/company context, and method notes. If a source is a related external video rather than an exact official recording, keep it framed as supporting evidence.
Transcript Status
Related video transcript availability: English auto-captions. Treat this as supporting context, not a recording of this exact scheduled session unless later confirmed. Not fetched yet.
People
Supporting Slides
- youtube OkEGJ5G3foU slides — extracted from the related public AI Engineer video.
Slide Evidence
- Slide-only cropped deck: youtube OkEGJ5G3foU dense slides (1 viable slide images).
- Related slide/OCR pages:
- youtube OkEGJ5G3foU dense slides
- youtube OkEGJ5G3foU reconstructed slides
- youtube OkEGJ5G3foU slides
- Slide-derived terms:
microsoft,contributions,fixes,awss,graphite,windsurf,mongobr,mdaily,augment,code,workos,unsloth,daniel,deep-dive,kernels,quantization,aaeoat,naan
Synthesis
Synthesized Breakdown
Special topics in Kernels, RL, Reward Hacking in Agents ## Conference Context - Date/time: 2026-06-29 · 2:20pm-5:30pm - Track/room: Workshops Day 1 · Track 3 - Speaker(s): Daniel Han - Session type/status: session · confirmed - Track: Workshops Day 1 - Room: Track 3 - Session type: session - Status: confirmed ## Session Description An advanced seminar (good prerequisites: Daniel's 2024 and 2025 hit AIE workshops, but all are welcome!) PLS WATCH: https://www.youtube.com/@aiDotEngineer/search?query=daniel%20han ## Media Evidence (Full Workshop) Reinforcement Learning, Kernels, Reasoning, Quantization & Agents — Daniel Han (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions). - Source video: youtube-OkEGJ5G3foU - Slide deck: [[youtube-OkEGJ5G3foU-dense-slides|Dense Slides: [Full Workshop] Reinforcement Learning, Kernels, Reasoning, Quantization & Agents — Daniel Han]] — no readable content slides after AI classification. - Additional slide evidence: [[youtube-OkEGJ5G3foU-slides|Slides: [Full Workshop] Reinforcement Learning, Kernels, Reasoning, Quantization & Agents — Daniel Han]], [[youtube-OkEGJ5G3foU-reconstructed-slides|Reconstructed Slides: [Full Workshop] Reinforcement Learning, Kernels, Reasoning, Quantization & Agents — Daniel Han]] - Slide-derived themes for youtube-OkEGJ5G3foU: fixes, chat, template, multiple, llama, research, google, github. ## Evidence Graph This evidence graph is generated from currently linked source material: official schedule text, related video pages, cached transcripts, visible slide text, dense/reconstructed slide pages, and AI slide-classification audits.
Speaker And Company Context
- Daniel Han — Co-founder at Unsloth.
Topics Covered
Derived Links And Source Material
- youtube OkEGJ5G3foU — related YouTube source page.
- youtube OkEGJ5G3foU slides — slide evidence.
- youtube OkEGJ5G3foU reconstructed slides — slide evidence.
- youtube OkEGJ5G3foU dense slides — slide evidence.
- youtube uIiA6DquRiE — related YouTube source page.
Novel Concepts / Clever Methods
- No highlighted novel concept has been detected yet.
Evidence Boundary
This synthesis is based on the official schedule and linked source pages. It should be revisited when exact session recordings or transcript-backed secondary sources are available.
Official YouTube Recording
- youtube uIiA6DquRiE — scheduled official AI Engineer YouTube premiere for 2026-07-17.
- Evidence status: transcript/slide enrichment pending.
- Boundary: use this recording as media evidence; keep date/time/room facts tied to the official schedule.