Pieces for Developers

🚨 We’re live on Product Hunt! 🚨 Pieces Long-Term Memory Agent (LTM-2) remembers everything you work on. No more lost code, forgotten links, or digging through Slack. We’d love your support! Drop a comment & share this post. 💙 🔗 https://lnkd.in/ggQfRwsA

Ever wondered what you can actually ask Pieces Long-Term Memory? 🤔 This guide walks through several real prompts you can use with Pieces LTM-2 to recall work, summarize info, and surface what actually matters. If you're using Pieces and not sure how to get started with prompting, give it a read👇 https://lnkd.in/ekiqpr8J #ai #artificialintelligence #copilot #chatgpt4 #claude #developers #coding #developerlife #gpt4 #LLMs #largelanguagemodels #machinelearningengineer #fullstackdeveloper #coding #softwareengineer

We tested 50 different LLMs. Here's what shocked us: 🧠 Most Accurate: Phi-4 by Microsoft (local!) hit 82% accuracy - beating out plenty of popular cloud models. ⚡ Fastest: Claude 3 Opus was super fast at 2.2s to first token. Local models like Granite 3 MOE 1B? Not so much. 🏆 Best Overall: GPT-4o (OpenAI) struck the right balance between accuracy, speed, and output. If you're choosing based on... - Accuracy & local execution: Go with Phi-4 - Raw speed: Gemini 1.5 Flash or Claude 3 Opus - All-around performance: GPT-4o Mini The real question: Are the big names still dominating, or are local models quietly catching up? 👀 Read the full benchmark breakdown by Jim Bennett here 👇 🔗 https://lnkd.in/erbjrrST #ai #artificialintelligence #copilot #chatgpt4 #claude #developers #coding #developerlife #gpt4 #LLMs #largelanguagemodels #machinelearningengineer #fullstackdeveloper #coding #softwareengineer

We tested 50 LLMs Pieces for Developers 👀 Results in the first comment 🔥

What if AI could handle 911 call reports while the operator listens? On a recent episode of the Pieces AI Productivity podcast, Daniele Bernardi (CEO Toolhouse) shared an interesting idea: an AI that fills out emergency reports in real time and prompts operators with the right questions—so they can stay focused on the caller. #coding #tech #programming #learntocode #programmerlife #softwareengineer #techjobs #techindustry #codinglife #learnprogramming #datascience #machinelearning #piecesfordevelopers #developers #developerlife #gpt4 #llms #largelanguagemodels

New to GitHub? This beginner-friendly guide walks through everything from setting up your account to making your first pull request. If you're just getting started with version control or open source, give it a read 👇 🔗 https://lnkd.in/eRXQ4JHf #coding #tech #programming #learntocode #programmerlife #softwareengineer #techjobs #techindustry #codinglife #learnprogramming

GitHub Copilot + Pieces = ❤️ GitHub Copilot helps you write code. Pieces helps you remember why you wrote it. This blog shows how combining the two can level up your workflow—with long-term memory, curated context, and fewer distractions. Check it out here and let us know what you think 👇

If you're still using off-the-shelf copilots, you're already behind. A while back, Jim Bennett wrote about how to build your own custom copilot using Pieces—complete with your own context, preferred models, and even a Star Wars theme (if that’s your thing). If you missed it the first time, now’s a good time to catch up 👇 https://lnkd.in/emGSNz9z

Great to see more shoutouts for Ellie Zubrowski's post on #MCP! And super proud to see Ellie's work featured alongside content industry greats like Martin Fowler in this digest.

Love to see “What the heck is #MCP? And why is everybody talking about it?” getting featured on Heavybit 🔥 🔗 https://lnkd.in/dSjvjVi4