I solved my study problems by talking to a goose
I used to study by rereading notes, and then I blanked in the exam hall. Did some research, and found that my experience isn’t isolated, and that passive review doesn’t force retrieval, so nothing sticks, and I knew I had to do something about it. That’s why I built Professor Goose. You pick a topic, explain it out loud to a goose, and he keeps probing until he understands you. Never gives you the answer, just keeps asking follow ups until a sound understanding is reached, which in turn makes you figure stuff out or realise you never understood your topic in the first place. Free to try, no…
In plain words
Professor Goose is a study tool where users explain topics aloud to an AI that asks follow-up questions until they demonstrate understanding. Rather than providing answers, the goose probes deeper to help users identify gaps in their knowledge and work through concepts themselves. Users can upload their syllabus for exam-specific questions. The tool is free to try without requiring an account, designed for students who find passive note review ineffective for retention.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
I used to study by rereading notes, and then I blanked in the exam hall. Did some research, and found that my experience isn’t isolated, and that passive review doesn’t force retrieval, so nothing sticks, and I knew I had to do something about it. That’s why I built Professor Goose. You pick a topic, explain it out loud to a goose, and he keeps probing until he understands you. Never gives you the answer, just keeps asking follow ups until a sound understanding is reached, which in turn makes you figure stuff out or realise you never understood your topic in the first place. Free to try, no account needed, upload your syllabus for exam board specific questions. Curious whether this approach resonates with others, it sure has for me.
More work this month
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Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
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Dev tools · May 2026 · github.com