The Complete Guide to Tool Selection in AI Agents

Same three analytics problems, three tools, eight dimensions, measured with real execution times and real agent prompts.

Developers looking to curb the cost of AI-powered coding tools have increasingly turned to the “Caveman” prompting style, which instructs coding assistants to communicate in blunt, telegraphic language and avoid conversational padding. The theory is simple: fewer words mean fewer tokens, translating into lower inference costs for organizations deploying AI agents at scale. A new test from IDE maker JetBrains confirms that terse prompting styles such as the viral open-source Caveman project can reduce token usage without hurting coding performance. However, the company found that the savings were far smaller than supporters claim. JetBrains used the Harbor open-source evaluation framework and tasks from SkillsBench for its test, and found that the Caveman technique reduced usage of output tokens by about 8.5%, far below its claimed 65%. The IDE-maker ran paired benchmarks across 86 real-world software engineering tasks in Claude Code, comparing coding sessions that used the Caveman pro

In June 2026, Google introduced the Open Knowledge Format (OKF), an open specification for how AI agents organise and exchange knowledge. An OKF bundle is just Markdown files, lightweight YAML metadata, and links between concepts, yet it challenges the assumption that every AI application needs embeddings and vector databases. Because the knowledge base is plain […] The post OKF: Redefining Knowledge Bases for AI Agents appeared first on Analytics Vidhya.

When I started evaluating browser agents, most of the conversation around me focused on multimodal models, computer-use systems and screenshot-based automation. Almost every framework I evaluated assumed agents needed to perceive the web the way humans do, visually, pixel by pixel. The more time I spent shipping agents against real web applications, the more I became convinced we were solving the wrong problem. AI agents would stall on checkout forms because a button had no ARIA role. They would waste seconds and thousands of tokens taking screenshots to figure out what was on the screen. The problem was never the Agent. It was that we kept treating the web as a visual surface, even though it already has a machine-readable interface. We have had one for decades. It is called the accessibility tree. The web already has a machine interface Most developers think of accessibility as a feature for people. Technically, accessibility required the web platform to solve a deeper problem: Exposi

... government of the people, by the people, for the people ... The cost of AI is dropping rapidly. GPT-4-class capabilities cost roughly $30 per million tokens in early 2023; today the same runs under $1, and some providers are pushing costs below $0.10. Across benchmarks, inference prices have fallen between 9x and 900x per year, with a median decline near 50x. Even frontier models are getting dramatically cheaper each generation, with open-source models following closely behind. And crucially, even if “Nobel-Prize-winning genius-level” intelligence isn’t here yet, the intelligence that suffices for the vast majority of knowledge work is here today, and getting cheaper by the month. At this rate, we are soon entering the era of virtually free intelligence—the kind that is more than enough for everyday knowledge work. Aditya G. Parameswaran—an Associate Professor of EECS and co-director of the EPIC Data Lab at UC Berkeley—together with his collaborators. It is part landscape survey an

AI vulnerabilities in prompt injection attacks could undermine trust in automated systems, posing significant risks to digital transactions. The post Zscaler researchers identify prompt injection attacks targeting AI agents for crypto payments appeared first on Crypto Briefing.

"The reality is, when you're optimizing for production, you start looking at a price/performance," Guillermo Rauch tells TechCrunch.

"One agent doing one task is certainly valuable, but multiple agents across the workflow really unlocks the value," said Karim Fadel.