<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>The Counter Brief</title><description>Decision-grade AI coverage for builders, founders, and operators. News, model deep-dives, explainers, and working playbooks, written for people who actually ship.</description><link>https://thecounterbrief.com/</link><language>en-us</language><item><title>What is an SDR? The sales development role, and how AI is reshaping it</title><link>https://thecounterbrief.com/explainers/what-is-an-sdr/</link><guid isPermaLink="true">https://thecounterbrief.com/explainers/what-is-an-sdr/</guid><description>An SDR fills the pipeline: they find and qualify prospects so account executives can close. What the role is, how it differs from a BDR, what it pays, and why AI is reshaping the job without eliminating it.</description><pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate><category>Explainers</category><category>sdr</category><category>sales development</category><category>bdr</category><category>ai sales</category><category>gtm careers</category><author>Adithya Sulaiman</author></item><item><title>What is conversation intelligence? A plain-English guide for revenue teams</title><link>https://thecounterbrief.com/explainers/what-is-conversation-intelligence/</link><guid isPermaLink="true">https://thecounterbrief.com/explainers/what-is-conversation-intelligence/</guid><description>Conversation intelligence records, transcribes, and analyzes your sales calls to show what works. What it actually does, how Gong and Chorus compare, and the affordable tier enterprise vendors don&apos;t mention.</description><pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate><category>Explainers</category><category>conversation intelligence</category><category>gong</category><category>chorus</category><category>call analysis</category><category>revops</category><author>Adithya Sulaiman</author></item><item><title>AI cold email in 2026: the playbook that survives the spam filter</title><link>https://thecounterbrief.com/playbooks/ai-cold-email-playbook/</link><guid isPermaLink="true">https://thecounterbrief.com/playbooks/ai-cold-email-playbook/</guid><description>AI made cold email easier to write and harder to land. Inbox providers now run AI filters that catch templated outreach, so the winning playbook uses AI for research and timing, not volume. The honest version.</description><pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate><category>Playbooks</category><category>cold email</category><category>outbound</category><category>deliverability</category><category>ai sales</category><category>lead generation</category><author>Nishtha Gupta</author></item><item><title>The honest AI sales stack: the 5-6 tools most GTM teams actually need</title><link>https://thecounterbrief.com/playbooks/honest-ai-sales-stack/</link><guid isPermaLink="true">https://thecounterbrief.com/playbooks/honest-ai-sales-stack/</guid><description>The average B2B team runs 12 sales tools. The best run 6. Here&apos;s the lean, layer-by-layer stack that covers a real go-to-market motion, and the categories you can skip.</description><pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate><category>Playbooks</category><category>gtm stack</category><category>sales tools</category><category>revops</category><category>consolidation</category><category>ai sales</category><author>Nishtha Gupta</author></item><item><title>AI SDR tools, honestly compared, and when you don&apos;t need one</title><link>https://thecounterbrief.com/tools/ai-sdr-tools-honestly-compared/</link><guid isPermaLink="true">https://thecounterbrief.com/tools/ai-sdr-tools-honestly-compared/</guid><description>The autonomous AI SDR market is full of bold promises, hidden pricing, and at least one genuine scandal. Here&apos;s what actually works, what the categories really mean, and how to tell whether you need one at all.</description><pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate><category>Tools</category><category>ai sdr</category><category>sales tools</category><category>outbound</category><category>revops</category><category>gtm</category><author>Adithya Sulaiman</author></item><item><title>Best AI lead generation tools, honestly compared (2026)</title><link>https://thecounterbrief.com/tools/best-ai-lead-generation-tools/</link><guid isPermaLink="true">https://thecounterbrief.com/tools/best-ai-lead-generation-tools/</guid><description>The AI lead-gen market has fractured into dozens of tools that each solve one piece of the puzzle. Here&apos;s what works, what it costs, and the one variable (data accuracy) that decides whether it pays off.</description><pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate><category>Tools</category><category>lead generation</category><category>b2b</category><category>ai sales tools</category><category>data accuracy</category><category>gtm</category><author>Adithya Sulaiman</author></item><item><title>Clay vs Apollo vs ZoomInfo: which data layer for which team</title><link>https://thecounterbrief.com/tools/clay-vs-apollo-vs-zoominfo/</link><guid isPermaLink="true">https://thecounterbrief.com/tools/clay-vs-apollo-vs-zoominfo/</guid><description>These three tools get compared as rivals, but they solve adjacent problems, and for most mid-market teams the right answer is a combination, not a winner. Here&apos;s the honest breakdown by team size and budget.</description><pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate><category>Tools</category><category>clay</category><category>apollo</category><category>zoominfo</category><category>data enrichment</category><category>revops</category><category>gtm</category><author>Adithya Sulaiman</author></item><item><title>5 vector databases, benchmarked: which one to actually ship</title><link>https://thecounterbrief.com/tools/vector-databases-compared-2026/</link><guid isPermaLink="true">https://thecounterbrief.com/tools/vector-databases-compared-2026/</guid><description>The five vector stores worth considering in 2026, what each costs, how fast it is, and the one question that decides most of them: do you even need a dedicated database, or is Postgres enough?</description><pubDate>Mon, 01 Jun 2026 00:00:00 GMT</pubDate><category>Tools</category><category>vector database</category><category>embeddings</category><category>rag</category><category>pinecone</category><category>qdrant</category><category>pgvector</category><author>Aditya Marin Gasga</author></item><item><title>Anthropic ships Sonnet 4.7 with native code execution</title><link>https://thecounterbrief.com/news/sonnet-4-7-native-code-execution/</link><guid isPermaLink="true">https://thecounterbrief.com/news/sonnet-4-7-native-code-execution/</guid><description>Sonnet 4.7 shipped this morning with Python execution baked directly into the API: no separate sandbox, no harness wiring, one new boolean parameter. Same model pricing as 4.6 plus a per-execution surcharge.</description><pubDate>Sun, 31 May 2026 00:00:00 GMT</pubDate><category>News</category><category>anthropic</category><category>sonnet</category><category>claude</category><category>tool-use</category><category>launch</category><author>Aditya Marin Gasga</author></item><item><title>We left half the models off our pricing chart. Here&apos;s the fix.</title><link>https://thecounterbrief.com/models/the-frontier-isnt-just-american/</link><guid isPermaLink="true">https://thecounterbrief.com/models/the-frontier-isnt-just-american/</guid><description>The Counter Brief&apos;s pricing calculator shipped without DeepSeek, Qwen, Llama, or Mistral. A reader called it out. Here&apos;s what changed, the corrected pricing, and when each non-US model is the right pick.</description><pubDate>Sun, 31 May 2026 00:00:00 GMT</pubDate><category>Models</category><category>deepseek</category><category>qwen</category><category>llama</category><category>mistral</category><category>pricing</category><category>open-weights</category><author>Aditya Marin Gasga</author></item><item><title>Your stated cache hit rate is probably lying to you</title><link>https://thecounterbrief.com/models/your-cache-hit-rate-is-lying/</link><guid isPermaLink="true">https://thecounterbrief.com/models/your-cache-hit-rate-is-lying/</guid><description>Your dashboard says 90% cache hits. Your bill says otherwise. The gap is almost always three specific patterns inside the system prompt that don&apos;t show up in any log, and you can fix them in an afternoon.</description><pubDate>Sun, 31 May 2026 00:00:00 GMT</pubDate><category>Models</category><category>caching</category><category>opus</category><category>inference</category><category>cost analysis</category><category>production</category><author>Aditya Marin Gasga</author></item><item><title>What is an embedding, really?</title><link>https://thecounterbrief.com/explainers/what-is-an-embedding-really/</link><guid isPermaLink="true">https://thecounterbrief.com/explainers/what-is-an-embedding-really/</guid><description>A from-scratch explainer of what embeddings actually are, how they&apos;re compared, why they make modern search possible, and which model to pick in 2026, in about 15 minutes.</description><pubDate>Sun, 31 May 2026 00:00:00 GMT</pubDate><category>Explainers</category><category>embeddings</category><category>rag</category><category>vector-search</category><category>semantic-search</category><category>explainer</category><author>Aditya Marin Gasga</author></item><item><title>MCP, explained: the protocol quietly wiring AI into everything</title><link>https://thecounterbrief.com/explainers/what-is-mcp-protocol/</link><guid isPermaLink="true">https://thecounterbrief.com/explainers/what-is-mcp-protocol/</guid><description>The Model Context Protocol went from a quiet Anthropic release to industry-standard plumbing in under two years. Here&apos;s what it is, why every major lab adopted it, and where the hype outran the facts.</description><pubDate>Sun, 31 May 2026 00:00:00 GMT</pubDate><category>Explainers</category><category>mcp</category><category>model context protocol</category><category>ai agents</category><category>anthropic</category><category>integration</category><author>Aditya Marin Gasga</author></item><item><title>How to use AI to review a contract before you sign it</title><link>https://thecounterbrief.com/playbooks/ai-contract-review-playbook/</link><guid isPermaLink="true">https://thecounterbrief.com/playbooks/ai-contract-review-playbook/</guid><description>AI can catch the risky clauses, missing protections, and odd language in a contract in minutes, but only if you use it as a first-pass reviewer, not a replacement for judgment. Here&apos;s the actual workflow.</description><pubDate>Sun, 31 May 2026 00:00:00 GMT</pubDate><category>Playbooks</category><category>ai workflows</category><category>contracts</category><category>legal</category><category>productivity</category><category>sales</category><author>Adithya Sulaiman</author></item><item><title>The 5-minute prompt-cache audit your team will actually run</title><link>https://thecounterbrief.com/playbooks/the-5-minute-weekly-prompt-cache-audit/</link><guid isPermaLink="true">https://thecounterbrief.com/playbooks/the-5-minute-weekly-prompt-cache-audit/</guid><description>Most cache audits never happen because nobody owns them. Here&apos;s the version that survives: 5 minutes a week, one CSV file, and a GitHub Action that runs it whether the owner remembers or not.</description><pubDate>Sun, 31 May 2026 00:00:00 GMT</pubDate><category>Playbooks</category><category>caching</category><category>production</category><category>ops</category><category>github-actions</category><category>playbook</category><author>Aditya Marin Gasga</author></item><item><title>7 AI agents worth testing in 2026</title><link>https://thecounterbrief.com/tools/ai-agents-compared-2026/</link><guid isPermaLink="true">https://thecounterbrief.com/tools/ai-agents-compared-2026/</guid><description>Seven AI agents tested on the same task suite: Manus, Devin, Operator, GPT Agent Mode, Gemini Workspace, Replit, Claude Computer Use. Two are genuinely useful today; the rest need a specific use case.</description><pubDate>Sun, 31 May 2026 00:00:00 GMT</pubDate><category>Tools</category><category>agents</category><category>manus</category><category>devin</category><category>operator</category><category>claude-computer-use</category><category>comparison</category><author>Aditya Marin Gasga</author></item><item><title>The AI coding assistants actually worth using</title><link>https://thecounterbrief.com/tools/ai-coding-assistants-2026-compared/</link><guid isPermaLink="true">https://thecounterbrief.com/tools/ai-coding-assistants-2026-compared/</guid><description>Six AI coding tools, one honest conclusion: there&apos;s no single winner, and the best developers pair two. Here&apos;s what each is actually for, what it costs, and which combination fits your workflow.</description><pubDate>Sun, 31 May 2026 00:00:00 GMT</pubDate><category>Tools</category><category>ai coding</category><category>developer tools</category><category>cursor</category><category>claude code</category><category>github copilot</category><category>comparison</category><author>Aditya Marin Gasga</author></item><item><title>OpenAI&apos;s trillion-dollar IPO, explained</title><link>https://thecounterbrief.com/news/openai-trillion-dollar-ipo-explained/</link><guid isPermaLink="true">https://thecounterbrief.com/news/openai-trillion-dollar-ipo-explained/</guid><description>OpenAI filed confidentially for what could be the largest tech IPO ever, at a valuation near $1 trillion, while losing more than a dollar for every dollar it earns. Here&apos;s what&apos;s actually going on.</description><pubDate>Fri, 29 May 2026 00:00:00 GMT</pubDate><category>News</category><category>openai</category><category>ipo</category><category>ai business</category><category>chatgpt</category><category>valuation</category><author>Aditya Marin Gasga</author></item><item><title>Gemini 3.5 and Google&apos;s pivot from answers to action</title><link>https://thecounterbrief.com/models/gemini-3-5-answers-to-action/</link><guid isPermaLink="true">https://thecounterbrief.com/models/gemini-3-5-answers-to-action/</guid><description>Google&apos;s Gemini 3.5, launched at I/O 2026, is built around a single idea: stop answering questions and start completing tasks. Here&apos;s what actually changed and why it matters.</description><pubDate>Fri, 29 May 2026 00:00:00 GMT</pubDate><category>Models</category><category>gemini</category><category>google</category><category>ai agents</category><category>llm</category><category>google io</category><author>Aditya Marin Gasga</author></item><item><title>Grok 4.3: xAI&apos;s bet on cheap and fast over best</title><link>https://thecounterbrief.com/models/grok-4-3-cheap-and-fast/</link><guid isPermaLink="true">https://thecounterbrief.com/models/grok-4-3-cheap-and-fast/</guid><description>Grok 4.3 isn&apos;t trying to top the leaderboards. It&apos;s trying to be the model you can afford to run at scale, and on that bet, it mostly delivers. Here&apos;s where it fits and where it doesn&apos;t.</description><pubDate>Fri, 29 May 2026 00:00:00 GMT</pubDate><category>Models</category><category>grok</category><category>xai</category><category>ai models</category><category>llm</category><category>pricing</category><author>Aditya Marin Gasga</author></item><item><title>Your Opus 4.8 cache misses are self-inflicted</title><link>https://thecounterbrief.com/models/opus-4-8-prompt-caching-maximize-hit-rates/</link><guid isPermaLink="true">https://thecounterbrief.com/models/opus-4-8-prompt-caching-maximize-hit-rates/</guid><description>A 70% versus 95% cache hit rate isn&apos;t the model. It&apos;s whether you set a cache_control breakpoint and keep the prefix before it byte-identical, with every dynamic value pushed into the user turn.</description><pubDate>Fri, 29 May 2026 00:00:00 GMT</pubDate><category>Models</category><category>opus 4.8</category><category>prompt engineering</category><category>caching</category><category>cost optimization</category><category>anthropic</category><category>performance</category><author>Aditya Marin Gasga</author></item><item><title>GPT launches agent mode for everyone: here&apos;s what you can actually do with it</title><link>https://thecounterbrief.com/news/gpt-agent-mode-launch/</link><guid isPermaLink="true">https://thecounterbrief.com/news/gpt-agent-mode-launch/</guid><description>OpenAI flipped agent mode on for all Plus and Team accounts this morning. The capability is real; the practical use cases are narrower than the demo suggests.</description><pubDate>Wed, 27 May 2026 00:00:00 GMT</pubDate><category>News</category><category>openai</category><category>gpt</category><category>agents</category><category>launch</category><author>Aditya Marin Gasga</author></item><item><title>The 7 AI writing tools worth using in 2026, compared</title><link>https://thecounterbrief.com/tools/best-ai-writing-tools-2026/</link><guid isPermaLink="true">https://thecounterbrief.com/tools/best-ai-writing-tools-2026/</guid><description>We tested seven AI writing tools on the same set of tasks. Three are great, three are fine, and one is genuinely worse than nothing. Here&apos;s how they stack up.</description><pubDate>Tue, 26 May 2026 00:00:00 GMT</pubDate><category>Tools</category><category>writing tools</category><category>ai writing</category><category>comparison</category><category>claude</category><category>chatgpt</category><author>Aditya Marin Gasga</author></item><item><title>Why Opus 4.8 changes the cost-per-token math</title><link>https://thecounterbrief.com/models/opus-4-8-cost-per-token/</link><guid isPermaLink="true">https://thecounterbrief.com/models/opus-4-8-cost-per-token/</guid><description>Opus 4.8 lists at $5/MTok in and $25 out (a third of the prior Opus generation) with cache hits at $0.50. Here&apos;s what that does to the real per-request math for production teams.</description><pubDate>Fri, 22 May 2026 00:00:00 GMT</pubDate><category>Models</category><category>opus</category><category>anthropic</category><category>pricing</category><category>cost analysis</category><category>inference</category><author>Aditya Marin Gasga</author></item><item><title>What is an LLM, really?</title><link>https://thecounterbrief.com/explainers/what-is-an-llm-really/</link><guid isPermaLink="true">https://thecounterbrief.com/explainers/what-is-an-llm-really/</guid><description>A from-scratch explainer of how large language models actually work (tokens, attention, the inference loop, and what to make of it all) in 12 minutes.</description><pubDate>Fri, 15 May 2026 00:00:00 GMT</pubDate><category>Explainers</category><category>llm</category><category>transformer</category><category>attention</category><category>tokens</category><category>explainer</category><author>Aditya Marin Gasga</author></item><item><title>Use Claude to cut your writing time by 70%</title><link>https://thecounterbrief.com/playbooks/cut-writing-time-70-percent/</link><guid isPermaLink="true">https://thecounterbrief.com/playbooks/cut-writing-time-70-percent/</guid><description>A four-prompt workflow that turns a 4-hour blog post into a 75-minute one, without the soulless AI tells. Real prompts, real before/after.</description><pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate><category>Playbooks</category><category>writing</category><category>claude</category><category>workflow</category><category>productivity</category><author>Aditya Marin Gasga</author></item></channel></rss>