Missed a lecture? This AI agent at Bar-Ilan University helps students catch up
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Microsoft AI Blog5 min read
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What is MLPerf Endpoints, and why it matters to buyers
MLCommons9 min read
The product manager job AI wants is the one from 1931
In 1931, a junior executive at Procter & Gamble wrote an 800-word memo asking for two more hires. He wanted someone accountable for each soap brand: someone who tracked sales, ran the promotions, handled the packaging, and talked directly to the people buying the soap.
Bagel AI Blog9 min read
Backlog zero in 2026: definitions, the clearance math, and how to check a claim
There are four ways to empty a backlog and only one of them involves delivering software: ship the work, reject the requests, move the tickets into a different tool, or stop recording demand in the first place. Three of those produce a screenshot that looks identical to the fourth.
Bagel AI Blog12 min read
Survivorship bias in product decisions: how to measure what your roadmap misses
Ranking product requests by how many times they were mentioned is still the most common way I see roadmaps get built. Twenty-three mentions beats eleven, so twenty-three goes higher.
Bagel AI Blog18 min read
Introducing Everything AI: AI Product Opportunities, Discovery OS, and MCP. Build the Right Thing, Faster
Your coding agents ship fast and ship blind. Today that changes. Claude Code knows your codebase. Cursor knows your file tree. Codex knows the syntax of every language you’ve touched.
Bagel AI Blog6 min read
21% accurate, even with every tool connected: what Anthropic learned about AI and messy data
Anthropic connected their data to Claude and asked it real questions. The answers looked great. The kind you’d forward to your team. Then they checked. Claude was right 21% of the time. So they fed it thousands of past queries and confirmed it read them. Accuracy moved less than a point.
Bagel AI Blog9 min read
The PM and developer used to pass work across a wall. AI knocked the wall down. Now what?
For twenty years the product manager and the developer ran a relay. The PM gathered customer input, wrote the spec, and handed it over. The developer took the spec, made the technical calls, and built it. The PM checked the result against the intent. Then the baton went back.
Bagel AI Blog8 min read
How MCP is Changing The Way Product Teams Work With AI
MCP became the default way AI agents connect to external data in 2025. In 2026, it’s quietly rewriting how product orgs make decisions. Here’s what’s actually happening, and what engineering leaders should be building toward.
Bagel AI Blog12 min read
What is an Autonomous Product Decision Layer? A Guide for AI-Native Teams
Product teams are surrounded by AI tools that don’t share context. The autonomous product decision layer is the architecture that fixes that, and it’s how AI-native orgs ship the right thing at scale. What is an autonomous product decision layer?
Bagel AI Blog15 min read
Fast Doesn’t Mean Right. What the Anthropic Podcast Left Out About Product Decisions.
Cat Wu went on Lenny’s Podcast last week and described a product org that ships features in days, removes process barriers by default, and lets engineers go from a Twitter complaint to a shipped fix by Friday. It was a great conversation.
Bagel AI Blog16 min read
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