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AIAndrej Karpathy built hn-time-capsule, a tool that feeds each December 2015 Hacker News front-page article and its comment thread to GPT-5.1 Thinking for a retrospective analysis. The project, written with Claude Opus 4.5 in about three hours, processes 930 articles at a cost of about $58 and roughly one hour. Results include prescience and wrongness grades for commenters, and the project is hosted on his website with the intermediate data available for download.

AIGoogle's Gemini 3 Deep Think mode is now available in the Gemini app for Ultra users. The post says it uses parallel thinking for difficult coding and scientific tasks and builds on technology that reached gold-medal level at the ICPC World Finals and IMO.

AIDeepSeek-V3.2-Speciale is available through a temporary endpoint at the same pricing as V3.2, but without tool-call support. The endpoint remains available until Dec 15, 2025, 15:59 (UTC).

AIWindsurf has launched Codemaps, AI-annotated structured maps of a codebase powered by SWE-1.5 and Claude Sonnet 4.5, which users can generate from a task prompt using a Fast (SWE-1.5) or Smart (Sonnet 4.5) model. Codemaps links grouped code sections to exact lines and can be referenced in Cascade with @{codemap} to give agents more specific context.

AIThinking Machines is expanding free access to Tinker for researchers and instructors through a grants program. The program offers credits for scholars and students to fine-tune and experiment with open-weight LLMs.

AICognition introduces SWE-grep and SWE-grep-mini, fast agentic models trained with reinforcement learning for multi-turn context retrieval in coding tasks. The company says they match frontier coding models at retrieval while taking an order of magnitude less time, and they power the Fast Context subagent in Windsurf. The models issue up to 8 parallel tool calls per turn within 4 turns, and Cerebras serves SWE-grep-mini at over 2,800 tokens per second and SWE-grep at over 650 tokens per second.

Why it matters: The post explains the speed-intelligence tradeoff in agentic code search, showing how parallel tool calls and RL training change the cost of retrieving context for coding agents.

AICognition says Claude Sonnet 4.5 is available in Devin starting today, improving its planning performance by 18% and end-to-end eval scores by 12%. Cognition says the model's testing of its own code lets Devin run longer and handle harder tasks.

AICognition's Devin is now compatible with the Model Context Protocol (MCP), letting users connect favorite MCP servers through a new MCP Marketplace found in Settings. The source cites example uses including querying Datadog and Sentry logs, creating Notion docs, Google Docs, and Linear tickets, and interacting with Figma, Airtable, Stripe, and Hubspot.

AICognition launched the official DeepWiki Model Context Protocol server, which is free and requires no login or authentication. It gives programmatic access to ask_question, read_wiki_contents, and read_wiki_structure for GitHub repositories indexed on DeepWiki.com. Private repositories require a Devin account with GitHub connected, and open-source maintainers can apply for $500 in Devin credits.

Why it matters: The source names the three tools and the access path, showing how indexed GitHub repositories can be queried programmatically without login.

AICognition is bringing back its Devin Open Source Initiative, offering $500 in Devin ACU credits to open-source GitHub projects with over 100 forks. Projects below that threshold will still be considered. Eligible projects must have an OSI-approved license and be actively maintained, and maintainers can apply through a linked form.

AICognition has released Devin 2.1, which reports its confidence in completing tasks using green, yellow, and red ratings. The company says green scores led to twice the likelihood of a merged PR compared with red, and Devin now also answers codebase questions and scores Linear and Jira issues.

Why it matters: The post explains how Devin now shows confidence scores and asks clarifying questions, which changes how teams can decide which tasks to hand over.

AICognition has launched DeepWiki, a free public version of its Devin Wiki and Devin Search tools that helps developers understand codebases. Users can view docs for any repo by replacing github.com with deepwiki.com in the URL, and more than 50,000 top public GitHub repositories are already indexed. Private repositories require a Devin account.

AICognition has released Devin 2.0, a new agent-native IDE experience with a flexible plan starting at $20. The update lets users run multiple parallel Devins, each with its own cloud-based IDE, and adds Interactive Planning, Devin Search, and Devin Wiki.

Why it matters: The release adds planning, codebase search, and auto-generated wikis to Devin, showing how an agent can prepare work before executing it.

AICognition's February 2025 Devin update adds parallel batch edits, beta GitLab support, and Sonnet 3.7, which Cognition says is the best model it has tested for debugging, codebase search, and agentic planning. Devin is about 2x faster than in October 2024, taking about 7.8 minutes on average to complete junior developer tasks in Cognition's internal evaluations. Other changes include copy-paste in Devin's browser and proactive feedback on suboptimal prompts.

AICognition's January 2025 Devin update improves its ability to find relevant files and reuse existing code in repositories, with changes rolling out to all users. It also adds enterprise accounts for centralized management of multiple organizations, audio message support in Slack, and pay-as-you-go billing after monthly ACU capacity is used, starting January 9.

AICognition has made Devin generally available to all engineering teams, with subscriptions starting at $500 per month. Over the past two weeks, Devin was made about 10% faster and about 10% more cost-efficient, especially for tasks requiring many code edits. The update also adds fixes for stuck or hanging sessions, more options to customize filters and Slack notifications, and larger machine settings for disk, RAM, and CPU.

AICognition is launching the Devin Open Source Initiative, giving selected open source maintainers 500 free ACUs on a Devin Teams plan as part of Devin's general availability launch. The post shows Devin contributing pull requests to projects including Anthropic's MCP Inspector, Dagger, and nanoGPT, with maintainers still reviewing the results. Devin's GitHub integration forwards PR comments and CI checks to help refine changes, though the company warns a human should still verify final quality.

AICognition is making Devin generally available to engineering teams starting at $500 a month, with no seat limits and access to its Slack integration, IDE extension, and API. The post recommends starting with small frontend bugs, first-draft PRs for backlog tasks, and targeted refactors, and shares open-source PR sessions where Devin resolved issues for projects including Anthropic MCP, Zod, and nanoGPT.

Why it matters: The post shows concrete open-source PR examples and the tasks where Devin works best, helping teams judge where an autonomous coding agent fits their workflow.

AICognition's December 2024 Devin update lets users tag Devin in Slack threads and ask it to create PRs, with Devin automatically responding to PR comments and lint failures. The update adds Repo Knowledge that Devin generates by scanning repositories, an Agency setting that makes Devin propose plans before executing complex tasks, and a REST API for structured input and output. Devin also gained faster session startup and enterprise options such as Okta single sign-on.

AICognition's Devin gained a September 2024 update with MultiDevin, which lets a manager Devin delegate work to up to 10 worker Devins, currently available on the Enterprise plan. Devin now automatically responds to comments on its pull requests, suggests Knowledge additions, and can restore earlier checkpoints, and the company reports up to an 80% reduction in time for common tasks.

AIDevin's June 2024 update lets users directly operate its VSCode editor, terminal, and browser, and adds Playbooks for recurring engineering tasks. It also adds Knowledge sharing, Machine Snapshots that persist dev environments, event-driven triggers from Slack, GitHub, and Linear, a Secrets manager, and tools for verifying Devin's work. Access remains limited to a waitlist with weekly invite releases.

AICognition introduces Devin as an AI software engineer that can plan and execute complex engineering tasks with a shell, code editor, and browser. On SWE-bench, Devin resolved 13.86% of issues end-to-end, versus a previous state-of-the-art of 1.96%, on a random 25% subset of the dataset. Devin is in early access, with access available through a waitlist.

Why it matters: The post pairs Devin's end-to-end task demos with SWE-bench results against prior models, letting readers weigh the claimed capability against the evaluation setup.