matt abrams

🏗️ How HOT2000 Makes Understanding Code Pathways Simple Navigating SB12, Step Code, and Net Zero pathways can be confusing—especially with multiple compliance options. HOT2000 helps builders and designers visualize the best route for each project, reducing errors and saving time. 💡 The Challenge  ❌ Multiple code pathways can be overwhelming  ❌ Manual calculations risk compliance mistakes  ❌ Early design decisions may lock builders into suboptimal paths  ❌ Misunderstood pathways can cause redesigns or permit delays  🔧 The Solution: HOT2000  HOT2000, Canada’s official residential energy modeling software, provides clear guidance on code compliance by simulating performance under all relevant pathways.  Here’s how it helps:  ✅ Compares prescriptive, performance, and Net Zero pathways side by side  ✅ Shows energy and cost impacts for each compliance option  ✅ Highlights where early design choices affect code eligibility  ✅ Reduces the risk of costly redesigns or non-compliance  ✅ Produces clear reports for stakeholders and municipalities  🎯 The Result  A builder in Mississauga used HOT2000 to evaluate three compliance pathways for a 2-storey home. The software revealed the most cost-effective route met Step Code Tier 2 with minimal changes, avoiding a $7,500 mechanical redesign.  💬 Bottom line: HOT2000 makes code compliance straightforward, helping builders confidently select the best pathway for every project. 📥 Download your free guide:  👉 https://lnkd.in/g_wtUD2T  💼 Want clarity on code pathways for your next build?  Book a call: https://lnkd.in/g3QtQUMK 

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Agents tend to re-read datasets and export artifacts-- a lot. Egress costs add up, and iteration slows down. CrewAI + Tigris fixes that. Pointing CrewAI's S3 reader/writer tools at Tigris gets you: - As many reads as your agent needs, no cost penalty - A durable workspace across agents and runs - Built-in snapshots for recovering past state And when agents publish data used downstream, a highly available object store ensures consistent reads without spikes in bandwidth costs. It's storage that makes sense for how agents actually behave. Get the guide for connecting Tigris and CrewAI 👇

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Anthropic's Claude Code is the latest power agent landing in Slack, proving we're transforming into the Agentic Work OS. 💡 Agents and humans are partnering in real time—pulling context directly from conversations (like bug reports) into coding sessions to accelerate work. We're the place where innovative AI agents from Anthropic and others deliver intelligence right in the flow of work. Slack is where the AI-native enterprise runs. 🌐

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Groq just announced Compound is now generally available to everyone. The chief architect is not who you might expect. It is a Stanford sophomore who went from viral GitHub apps to leading Groq's agent product in under a year. This is the story of how Benjamin Klieger built the most exciting agentic architecture available today. Ben’s journey to Compound started early. In school, he spent his time building. Social platforms and trade tools, experiments that taught him a deeper truth: The most intelligent systems are defined by making the right decisions at the right time. During that time, he built his second startup: a writing app called Clara. He noticed the problem  for students wasn’t writing essays. It was learning reflective and logical thinking. Clara lived in Google Docs, asking Socratic questions. When it was acquired, Ben saw AI as a force multiplier for tools. In 2024, he witnessed Groq speed firsthand. He assumed someone would build an instant book generator on top of it. He waited. Nobody did. So he launched Infinite Bookshelf: give a topic and a 15-page book appeared in seconds. Groq noticed Ben’s work. How could they not? When they reached out, Ben showed up to the meeting with live demos instead of a résumé. He left with an internship and a mandate. Within six months his projects had over tripled the number of stars on Groq GitHub projects. He learned AI wasn’t just about answering faster, but about creating systems that handle complexity and scale. Ben wanted to prove that the next generation of AI could go further than anyone thought possible. And he wanted to show Groq could be the one to build it. Then came what he called g1, a Groq-powered reasoning app, built within 24 hours of OpenAI’s o1-preview. It hit 4,000 GitHub stars, far more than any Groq repo had ever received. By late 2024, every lab had begun to build compound AI systems that execute search and code. Models were becoming agents. But Ben noticed they were expensive and slow. Latency kills agents. Every tool call, every context switch, every decision added seconds that stacked into unusable experiences. The solution was not better prompts, it was better architecture. When asked to host g1 and pair it with tools, Ben saw an opportunity. Instead of sending every request over distant APIs, server-side tools ran close to inference. Model routing ensured the best models were used. This is where Compound emerged. Ben was promoted to Compound AI Lead and put in charge of the product. The Compound team grew. Iteration with users made it stronger. Adoption followed quickly. Compound became default in GroqChat. Over 100,000 developers used it. Over 5 million requests were serviced. Groq making Compound generally available is a turning point for agentic AI. It exists because of Ben’s journey to build what was missing. Try Compound today to experience the next generation of agents. 🔗 https://chat.groq.com 💻 https://github.com/groq Benjamin Klieger

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