4,912 stories
A founder's guide to turning order and payment exports into a dashboard you can actually use, with a video walkthrough and a copyable prompt.
How AI agents are changing expense management in 2026: what they automate, who is building them, and where you still keep a human in the loop.
Campfire and Digits are both AI-native accounting platforms, but they’re built for different operating models. Campfire gives finance teams a configurable AI workforce inside an ERP. Digits gives accounting firms a continuous accounting operation across their client books.
It starts with a Slack thread that should have taken 30 seconds. Can someone pull last week’s Instagram numbers? What is going out for Acme tomorrow? Is the launch post approved yet? Then the thread goes quiet.
We had to upgrade our 56TB Aurora Postgres cluster by 31 July without taking Trigger.dev down. Instead of moving the database, we made the problem smaller: new runs and the control plane went to PlanetScale, and the old runs stayed behind.
Every boundary you draw removes a signal your tooling was relying on. That is a structure problem, not a search problem. The post Good Architecture Deletes the Signals Your Agent Depends On appeared first on Towards Data Science.
AI is changing expectations around infrastructure and operations, including Kubernetes management. When models run close to the data they use, The post The rise of agentic AI on Kubernetes: unleashing the new infrastructure layer appeared first on The New Stack.
Nathan Labenz and Prakash Narayanan review key AI developments with five experts, discussing multi-agent coordination risks, AI safety funding bottlenecks, GPU compute markets, sensor foundation models, and robotic drug testing.
Jeremy Howard published version 2 of the llms.txt specification on August 10, 2026 — the first significant revision since he originally proposed the format in September 2024.
Set up LLM evaluation with a golden dataset, useful metrics, CI gates, regression tests, and production feedback. A practical workflow for engineers.
You give an LLM long-term memory by adding a layer outside the model that decides what is worth keeping from each conversation, stores it against the right person, updates it when a fact changes, and puts only the relevant slice back into the prompt on the next call.
For agent memory, neither wins on its own: vector search finds past statements that mean something close to the current question, and a knowledge graph connects facts through the same person or company and tells which of two conflicting facts is current.
A graph database stores data as nodes and relationships and answers questions by following those relationships instead of joining tables; use one when your main questions are about paths across connected data, and keep a relational database for records and reporting.
As of 26 September 2026, the best open-source embedding model for most teams is Qwen3-Embedding, which is Apache 2.0, reads 32K tokens and ranks 5th on MTEB English v2 and 4th on MTEB Multilingual v2.
ChatGPT Voice now triggers tasks by voice – but does it replace a dedicated AI phone agent for real customer calls? A detailed comparison
Reilly Haskins, Rif A. Saurous, Nate Rush, Neev Parikh, and Beth Barnes lay out the claims that would need to hold for their per-action blocking monitor to be effective, the evidence for each claim, and the gaps that remain.
#JEV #AgenticAI #AIEngineer Curated Structured Learning program : https://balajichippada.com/ 🌐 Free AI Engineer Roadmap 2026: https://balajichippada.com/roadmap 🔗 Join the WhatsApp Community https://chat.whatsapp.com/EoQWZa870wG3TzUeOpH54c This is to bring together serious and like-minded…
Score AI agents for customer service on architecture, observability, and pricing incentive, not on a resolution-rate demo.
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