Long-time Python, ML, AI and data builders show how they're actually using agents today. Not vibe coding. Not demos. The real workflows: agent skills, harnesses, voice-memo memory, background reviewers, from people whose software you've been using for years.
Chip Huyen showed a runner where a strong model plans and reviews while cheaper agents work across providers. Tim Hopper showed how he builds and deploys software from his phone while walking, then asks the agent to email him when it finishes.
Mining agent histories into reviewed skills, keeping coding agents inside verifiable loops, benchmarking complete model-and-harness combinations, and maintaining a multilingual knowledge graph on a nightly schedule.
Running a company on agent-readable context, handwritten AGENTS.md files, telemetry agents can inspect, an always-on personal agent, and workflow code with human checkpoints.
Rook, Raw2Draft, MCut, Conductor, private skills, and the 90/10 handoff.
Skill scepticism, plan review, implementation review, agentic search, and hidden holdout tests.
Research memory, local boxes, debug panes, live notebooks, video generation, and code repair.
Prompt refinement, eval-driven charts, human-in-the-loop EDA, and local-first inference.
RoboRev, agent memory, personal commands, and LLM-as-judge chart checks.
GREG CECCARELLIEP 07Lore, hidden completion checks, and a new agentic software lifecycle
HAN-CHUNG LEEEP 07SkillsBench, verifiable trajectories, and nightly multilingual memory
A selection of skills and workflows from the streams, packaged into the companion repo.
Episode announcements, the workflows we cut for time, and what long-time builders are actually doing with agents. Free, no spam.
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