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On Monday, Warp’s AI agent landed the #1 spot on Terminal-Bench, over 20% ahead of the previous leader, Claude Code, and clocked 71% on SWE-Bench Verified (top 4).

How did Warp become one of the most powerful AI dev agents?

Some highlights:

1. Deep upfront task planning – sets the agent up for success

2. Long-running commands – something no other tool can support

3. Warp Rules – provides critical guardrails for agents

Get the full story and try Warp’s state-of-the-art development agent for yourself!

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NEWS UPDATES

Google has opened preview access to Gemini CLI, an AI agent that runs directly in the terminal and taps the Gemini 2.5 Pro model’s 1-million-token context window. Developers can ask natural-language questions, generate or fix code, and even invoke Veo and Imagen for media tasks, all under a generous free quota.

If your teams spend time in the command line, this could speed debugging and prototyping without extra IDE plugins, which is worth a small pilot for engineering productivity.

→ More details about Gemini CLI

Anthropic’s latest update lets any Claude user describe an idea and have the chatbot generate a working application inside the interface. Early testers have spun up AI games, analytics dashboards, and multi-agent workflows, with API hooks for further automation.

Citizen-developer tools are maturing fast; consider giving product or ops teams a sandbox to test low-code AI apps before IT formalizes support.

→ More details about Claude’s app builder

DeepMind introduced AlphaGenome, a model that reads up to one million DNA base pairs and predicts thousands of regulatory properties, including effects of rare mutations in non-coding regions of the genome.

The bigger signal is AI’s leap from text to complex scientific sequences. Expect similar domain-specific models (chemistry, materials) that could open new data-driven product lines in other industries.

→ More details about AlphaGenome

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STRATEGIC AI DECISION

PS. You just read the answer in the news above :)

MARKET

PROMPT TUTORIAL

The Earnings Call Analyzer agent helps users extract insights from public company earnings reports without needing to read long transcripts.

In this example, we selected Apple (AAPL) for Q1 2025 and asked: “What were the 3 main business challenges mentioned?” The agent instantly summarized the report, highlighting macroeconomic pressures, competitive issues in China, and inventory adjustments. It’s a quick way to get boardroom-ready summaries with just one question.

Here is the prompt:

You are a pro business insights extractor. Given a company’s quarterly earnings report, your task is to identify and summarize the 3 main business challenges the company mentioned. Analyze the report with attention to revenue performance, operational constraints, market shifts, or leadership commentary. Focus only on challenges explicitly stated or clearly implied, and avoid speculation. Use this prompt by replacing the placeholders: [company type or description], [report type], and [time period].

Company type or description: {company_name}

Report type: {report_type}

Time period: {time_period}

P.S. You can still get the Prompting Playbook (free for you)