“There's An AI For That lays out a 3-step AI system design—decouple planning from building to prevent context rot, keep static rules minimal and load skills on demand, and fix system-level issues instead of patching model bugs—arguing that the surrounding system, not the model...”

#10 𝕏 There's An AI For That lays out a 3-step AI system design—decouple planning from building to prevent context rot, keep static rules minimal and load skills on demand, and fix system-level issues instead of patching model bugs—arguing that the surrounding system, not the model...

“There's An AI For That launched a Hyperagent integration with Google’s Gemini Omni API that lets agents ingest raw video and automatically output enhanced footage, slashing the complexity, cost, and speed barriers of traditional video workflows.”

📝 𝕏 There's An AI For That launched a Hyperagent integration with Google’s Gemini Omni API that lets agents ingest raw video and automatically output enhanced footage, slashing the complexity, cost, and speed barriers of traditional video workflows.

“There’s An AI For That released WonderZoom (paper: arxiv.org/abs/2512.09164, code/demo: wonderzoom.github.io), an open-source framework for hierarchically zooming into model activations and attention maps to explore multi-scale reasoning.”

#21 𝕏 There’s An AI For That released WonderZoom (paper: arxiv.org/abs/2512.09164, code/demo: wonderzoom.github.io), an open-source framework for hierarchically zooming into model activations and attention maps to explore multi-scale reasoning.

“There’s An AI For That released WonderZoom (paper: arxiv.org/abs/2512.09164, code/demo: wonderzoom.github.io), an open-source framework for hierarchically zooming into model activations and attention maps to explore multi-scale reasoning.”

#21 𝕏 There’s An AI For That released WonderZoom (paper: arxiv.org/abs/2512.09164, code/demo: wonderzoom.github.io), an open-source framework for hierarchically zooming into model activations and attention maps to explore multi-scale reasoning.

“#12 𝕏 There's An AI For That built Code Review Graph, using Tree-sitter to map your repo so Claude only loads relevant files, delivering a 49× reduction on monorepos.”

#12 𝕏 There's An AI For That built Code Review Graph, using Tree-sitter to map your repo so Claude only loads relevant files, delivering a 49× reduction on monorepos.

“#5 𝕏 There’s An AI For That launched a free, open-source AI that uses only Wi-Fi signal reflections—no cameras or sensors—to reconstruct real-time, full-body poses through walls, in the dark, and across rooms.”

GenAI PM Daily May 31, 2026 GenAI PM Daily 🎧 Listen to this brief 3 min listen Today's top 19 insights for PM Builders, ranked by relevance from X, LinkedIn, Blogs, and YouTube. Josh Pigford’s 3-phase AI-agent build process #1 𝕏 NVIDIA AI launched DynoSim, a full-Rust, workload-driven simulator for the Dynamo serving stack that models your entire inference pipeline on one virtual timeline and screens thousands of deployment configurations in high-fidelity simulation. #2 𝕏 Clement Delangue hails AI Security Institute’s open release of its evals, datasets and models on Hugging Face, empowering researchers worldwide to scrutinize, reproduce and build on their AI safety work. #3 𝕏 Guillermo Rauch rolled out per-API Key spend caps on AI Gateway, letting users set budget limits for each key to better control costs. #4 in Peter Yang highlights how Josh Pigford—fresh off a $4M exit— is solo-building five AI-agent products, using a 3-phase build process, adversarial code reviews with Opus + GPT-5.5, and a “but for real” AI bug-catching hack. #5 𝕏 There’s An AI For That launched a free, open-source AI that uses only Wi-Fi signal reflections—no cameras or sensors—to reconstruct real-time, full-body poses through walls, in the dark, and across rooms.

“#18 𝕏 There’s An AI For That showcases AI-driven non-contact solutions like camera-free elderly fall detection, location-aware smart home automation, and health monitoring of breathing, movement patterns, and posture.”

GenAI PM Daily May 31, 2026 GenAI PM Daily 🎧 Listen to this brief 3 min listen Today's top 19 insights for PM Builders, ranked by relevance from X, LinkedIn, Blogs, and YouTube. Josh Pigford’s 3-phase AI-agent build process #1 𝕏 NVIDIA AI launched DynoSim, a full-Rust, workload-driven simulator for the Dynamo serving stack that models your entire inference pipeline on one virtual timeline and screens thousands of deployment configurations in high-fidelity simulation. #2 𝕏 Clement Delangue hails AI Security Institute’s open release of its evals, datasets and models on Hugging Face, empowering researchers worldwide to scrutinize, reproduce and build on their AI safety work. #3 𝕏 Guillermo Rauch rolled out per-API Key spend caps on AI Gateway, letting users set budget limits for each key to better control costs. #4 in Peter Yang highlights how Josh Pigford—fresh off a $4M exit— is solo-building five AI-agent products, using a 3-phase build process, adversarial code reviews with Opus + GPT-5.5, and a “but for real” AI bug-catching hack. #5 𝕏 There’s An AI For That launched a free, open-source AI that uses only Wi-Fi signal reflections—no cameras or sensors—to reconstruct real-time, full-body poses through walls, in the dark, and across rooms.

“#12 𝕏 There's An AI For That launched LlamaParse, which converts messy real-world PDFs into clean markdown so LLMs can reason across hundreds of documents at scale.”

This item attributes the launch of LlamaParse to the company/platform.

“There's An AI For That launched SubQ, an architectural fix enabling models to handle up to 12 M token contexts without forgetting, hallucinating, or crawling to a halt.”

#8 𝕏 There's An AI For That launched SubQ, an architectural fix enabling models to handle up to 12 M token contexts without forgetting, hallucinating, or crawling to a halt. It installs in one line on Claude Code, Codex, or Cursor at just a fraction of Opus’s cost.

“#2 𝕏 There's An AI For That launched Context Mode, piping MCP tool output into a SQLite database so Claude can query it like a DB, slashing logs and GitHub payloads by 98%.”

GenAI PM Daily May 03, 2026 GenAI PM Daily 🎧 Listen to this brief 3 min listen Today's top 14 insights for PM Builders. OpenAI Symphony + Playwright harness: 5× coding agents #1 𝕏 Jason Zhou demonstrates that pairing OpenAI Symphony with a codebase harness (Playwright CLI, Boot skill, WORKFLOW.md) can 5× coding agent outcomes, and provides a 12-minute walkthrough to set it up. #2 𝕏 There's An AI For That launched Context Mode, piping MCP tool output into a SQLite database so Claude can query it like a DB, slashing logs and GitHub payloads by 98%. #3 𝕏 Santiago shared 20 actionable Claude Code shortcuts—like Esc + Esc to rewind, `/rewind` for backtracking and `/insights` for instant summaries—to help PMs streamline prompt workflows and debug faster. #4 𝕏 Sebastian Raschka showcases his LLM Architecture Gallery comparing open-weight Qwen3.6 (35B) with Kimi-K2-6, noting that Qwen3.6 is the smaller open model and that a larger, more capable API-only Qwen3 variant is also available. #5 𝕏 Peter Yang highlights Ravi’s 3-layer AI prompt framework—functional, visual, and data—and argues the often-overlooked data layer is crucial for creating flexible, high-quality app prototypes. #6 𝕏 Harrison Chase warns that while swapping model providers is straightforward, changing inference/training harnesses is much harder due to vendor lock-in—and urges the development of open harnesses to keep users flexible. #7 𝕏 Peter Yang gives Codex and Claude Code full access to his Mac and Google Workspace CLI to audit boot-up apps, downloads, and Google Drive—always requesting a cleanup plan first—and now his files “spark joy.” #8 𝕏 Sam Altman says that although he’s been focused on making AI models cheaper and faster, simply improving their intelligence remains the top priority. #9 𝕏 Jason Zhou set up dedicated human-only Slack channels to keep conversations natural and calls for per-channel task outcome tracking, citing Crewlet’s experiment with a Slack bot plus dashboard for work output monitoring and collaboration. #10 𝕏 Teresa Torres warns that anyone can build an AI prototype in a day but teams massively underestimate the work to make it production-ready. #11 𝕏 Dharmesh Shah argues that differentiating durable value with a frontier model + harness is harder than leveraging deep, years-long accumulation of data and context. He also doubts we’re heading toward an AI “-mageddon.” #12 𝕏 Garry Tan likens Hermes Agent to a rock-solid Honda Accord and OpenClaw to a high-performance Ferrari that demands roadside tinkering but delivers exceptional power. #13 𝕏 Harrison Chase warns that memory and integrations are still tightly coupled to the agent harness—only agents.md and skills hint at any open standard. #14 𝕏 There's An AI For That launched Claude Token Efficient—a one-file (CLAUDE.md) tool that enforces terse responses across all sessions in a repo, boasting the lowest-effort install on the list.