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Wispr Flow [5] lets you speak detailed prompts instead of typing short ones. Explain the full context, the constraints, the edge cases, in the time it takes to type a sentence. 4x faster than typing.
Moonshot has launched Kimi K3, a 2.8-trillion-parameter multimodal model with a 1-million-token context window and optimizations for faster long-context decoding and agentic coding. The model is available through Kimi's products and API, with open weights scheduled for release on July 27.
Alphabet shares fell 4% after a report said Google had delayed Gemini 3.5 Pro while working to improve its performance, particularly for coding. Google said the model remained in partner testing alongside an upgraded Flash model and other releases.
Bionic is an AI agent for coding, research, and document management with open models, offering local and cloud options for privacy and cost control. It supports offline voice transcription with Voxtral by Mistral AI and excels at coding by inspecting codebases and solving issues with models like GLM 5.2. Bionic enhances productivity by working with various documents while ensuring security with sandbox environments and native web search integration.
Harness Handbook is a behavior-level map for coding-agent harnesses, connecting plain-language questions about execution, permissions, and safety to the exact prompts, tools, state logic, configuration, and telemetry that implement them.
Anthropic uses a six-step process with Claude Code for large-scale code migrations, focusing on creating a rulebook, analyzing dependencies, and stress-testing translation rules. It deploys multiple agents to translate, review, and fix code iteratively, and emphasizes using adversarial reviewers and mechanical verification for efficient migration.
GPT-5.6 splits Codex work across Sol for ambiguous, high-value problems, Terra for everyday implementation, and Luna for fast, bounded tasks. Sol Ultra adds deeper reasoning and multi-agent coordination, while clear prompts should specify goals, context, boundaries, and completion checks.
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Most failure-handling logic is complex, fragile, and hard to test. This Temporal white paper [14] shows you 2 distinct patterns to take component failure in stride without constraining application structure. Learn how to implement these patterns using the same open
Schema is a harness that makes frontier models play like physicists. It can help frontier models achieve 99% on ARC-AGI-3 Public. ARC‑AGI‑3 gives agents a game environment without an explanation of what it is seeing. Schema makes agents write each game's mechanism as an executable program, test it against reality, and plan inside it. It controls how observations are turned into a working model of a game, how predictions are tested against the interaction history, and how plans are executed and revised.
NVIDIA released three open embedding models for RAG, agentic retrieval, code search, and memory, led by an 8B model that ranked first overall on RTEB.
Embeds GitHub Copilot agents into custom applications and developer tools.
Model routing is a hot topic because nobody wants to pay frontier prices for every token. The best routing is deeply task-specific. The more narrowly you focus on a single workflow, the more alpha there is to exploit in terms of both accuracy and cost. The problem is figuring out which model clears the bar for which task, subject to cost/latency constraints.
Replit engineers have tripled code output without sacrificing quality, thanks to an innovative system of AI agents. These agents handle tasks like reviewing pull requests, investigating incidents, and analyzing data, enabling engineers to focus on strategic initiatives.
Nvidia-backed Fireworks secured a $17.5 billion valuation, driven by demand for cheaper AI models as companies explore open-source options.
Google added integrations with Instacart, Canva, and YouTube to AI Mode, allowing users to complete tasks across supported apps from its conversational search experience.
Ramp has expanded its AI Token Spend Management product to give finance teams clear insights into AI spending across providers like OpenAI, Anthropic, and Google's Gemini.
Google has rebranded NotebookLM as Gemini Notebook, expanding its integration across the Google ecosystem, including the Gemini app and Google Search.
The Unicode Consortium is set to unveil nine new emojis—including Lighthouse, Eraser, Pickle, Monarch Butterfly, Meteor, and Cracked Smiling Face—ahead of World Emoji Day on July 17. These designs, shared by Unicode Emoji Subcommittee Chair Jennifer Daniel, are expected to reach keyboards by next spring, with some existing emojis redesigned for visual distinction. The Cracked Smiling Face, originally proposed as "Smiley Face with Squinting Eyes," is predicted to become the standout favorite among the new additions.
Apple's iPhone 18 Pro is expected to launch in September, potentially as part of a new release strategy where Pro models arrive months before the standard iPhone 18. Rumors point to a refined design with a smaller Dynamic Island, a cleaner rear panel, a faster 2nm A20 Pro chip, a variable-aperture main camera, a larger battery, and improved AI performance, though the long-rumoured under-display camera still isn't expected. Pricing is likely to increase from the current $1,099 starting point, with estimates ranging from $1,199 to $1,299, while all details remain based on leaks and speculation.
Google Vids is adding custom AI avatars that let users create videos starring a digital version of themselves using a selfie and voice recording. The update also brings Gemini Omni to Vids, enabling video generation from prompts and reference images, along with background swaps, lighting fixes, effects, and step-by-step edits. While positioned as a Google Workspace tool for business videos, the new avatar and editing features move Vids closer to AI video platforms like HeyGen, Synthesia, Captions, and D-ID.
As AI-generated media becomes harder to distinguish from human work, trust is eroding, prompting creators to reveal their process, tools, and behind-the-scenes work as proof of authorship. Provenance matters most for expressive work like art or film, where authorship shapes meaning, but barely registers for functional tools like transaction interfaces. The real challenge isn't documenting every step of creation, but recognizing when audiences actually care and designing disclosure accordingly.
AI interfaces are at a stage similar to the early web, with platforms introducing incompatible interaction patterns that create inconsistency, increase development costs, and make products harder for users to trust and adopt. The solution is to establish shared standards for AI interactions—such as how systems communicate confidence, cite sources, request permission, and hand tasks back to users—following the same principles that made the web more accessible, interoperable, and maintainable. Rather than creating isolated conventions, designers and developers should collaborate through existing standards bodies and open protocols to build a consistent AI ecosystem before proprietary approaches become entrenched.
Koto has launched CcType, a new type foundry that makes its design expertise available beyond its client work, following the same philosophy behind its free educational platform, Seasoned. Rather than releasing a large catalogue, the foundry debuts with a single typeface, CcTimeline, reflecting a deliberate "build in public" approach focused on quality, experimentation, and accessibility, with pricing aimed at freelancers and small studios. The initiative was inspired by the strong demand for Koto's open-source client typefaces and represents a broader effort to democratize high-quality design while continuing to refine the studio's craft in public.
Generate everything from short ads to full-length stories in minutes.
Stop exporting annotated screenshots from Figma. Annotate your rendered DOM with data-part and get an interactive, synchronized anatomy panel — in plain HTML, Astro, or Storybook.
Connect your data, automate the work, and turn it into visuals you can understand and share.
Product design drifted from crafting interfaces toward workshops, strategy decks, and process, with senior status increasingly tied to distance from actual design tools like Figma. This shift produced bloated design systems and impersonal products, prompting companies to question whether costly design teams were actually improving outcomes. AI's arrival now challenges designers to prove they can create what AI cannot, pushing the profession back toward genuine craft rather than process for its own sake.
Facebook's interface gradually shifted from a predictable, chronological, user-controlled feed to an algorithm-driven system optimized for engagement over usability. Feature additions like groups, marketplace, and reels fragmented the once-coherent experience, increasing cognitive load without transparent explanation of personalization. This reflects a broader design lesson: products don't fail suddenly but drift through small, individually reasonable decisions that erode clarity and trust over time.
Rumors suggest the iPad Mini 8, expected late 2026, will gain an OLED display and an A19 Pro chip, boosting appeal for creatives doing digital art and editing.
Fold7Design created the branding for the UK's National Year of Reading 2026 around the idea of "Go All In," encouraging people to discover reading through their existing interests—such as sport, gaming, music, or fashion—rather than treating it as a duty.
The Bay Area pulls almost 2.5x the capital of the entire New York ecosystem across every category combined. Value concentration in AI and B2B is more concentrated now than it was five years ago. Two metros combined take 72% of B2B dollars. Talent and capital didn't disperse - the narrative got ahead of the numbers.
Agents at Replit now investigate production incidents, review pull requests, answer questions, analyze business data, triage support tickets, research sales accounts, and improve the systems that power the Replit Agent itself. The company's expanding system of agents takes goals from people, gathers context, performs work, checks the results, and escalates when human judgment is needed. People still decide on which problems matter, make difficult tradeoffs, exercise taste, and take responsibility for the outcome, but they increasingly do not perform every step required to get there.
Companies selling data to frontier AI labs know the cash is real, but the contracts are not forever. There are six categories of products being sold to frontier labs: hours, judgment, worlds, verdicts, bodies, and rights. Each generation of models graduates past the data that trained it, so labs need fresh data to keep pushing the frontier.
The point of the onboarding process is to teach users how to use your product. The MCP onboarding process should give agents a step-by-step guide on how to walk users through their first time using your product. Agent-native support can be better than founder support. The field of agent-first interfaces is still in a nascent stage, so a lot can still change.
Cerebras' employees ask the company's internal knowledge base more than 15,000 questions every day. It has become one of the company's most widely adopted internal tools since launching 3 months ago. The knowledge base is used by humans, automations, and agents. This post details how Cerebras Knowledge was built.
Someone can discover you in ChatGPT, Google your company a week later, and show up in GA4 as Direct traffic. That is why AI search can look tiny in your analytics even when customers are using it. Only about 1% of people click citations in Google AI Overviews, and 70.6% of AI-referred visits are recorded as Direct. Before deciding AI search is doing nothing, add ChatGPT, Claude, Perplexity, and Google AI to your "How did you hear about us?" question. Then tag the same answers in your sales calls.
1Password for Claude is built on a zero-exposure architecture that only grants access at runtime. Claude never sees the vault item, password, or one-time code, and access is scoped to the current task and ends when the task is complete. Access requires user-consented biometric approval, and credentials are injected directly into the page. 1Password for Claude is now available for Mac for business, family, and individual plans.
Muse Spark 1.1 is now available on OpenRouter for developers in the US. Muse Spark is a multimodal reasoning model from Meta. Built for agentic tasks, it accepts text, images, video, audio, and PDF documents and returns text. The model has a 1-million-token context window. It is designed to orchestrate multi-agent workflows and supports structured output, parallel function calling, built-in search with citations, and configurable reasoning effort.
Natural language is a far more useful form of input than the indirect signals the industry had to live with over the past 20 years. It allows companies to read exactly what users want to accomplish and whether or not they're satisfied. Natural language inputs, paired with other signals, can help companies see the relationship between the performance of agents and revenue. Agent observability is not only an engineering concern - CEOs, product leaders, and customer-facing teams should be reading this data too.
Venture firms can no longer rely on IPOs, M&A, or secondary buyers to convert portfolio markups into DPI. Healthy private companies may need cash-flow-driven buybacks and capital return programs, supported by duration-matched credit, to create liquidity without sacrificing growth.
It's an open secret that AI agents aren't reliable because they're stochastic, prone to lying, expensive, and make mistakes. Businesses are responding by selling better cages, but AI is not deterministic. Nobody survived the cloud wars by having a better shovel - they survived by building moats. These companies are competing with model improvements, and the models will eventually win.
Open source AI is funded by companies shipping a deliberately unremarkable, general-purpose base cheaply and letting customers build value through customization.
If a customer says "interesting" after your demo, they are probably about to ghost you.
Product executives, especially those skilled in building with modern tools, are now commanding salaries akin to pro-athletes due to high demand and scarcity.
Investors, LLMs, and probably your friends all say "taste" is the only thing left to defend now that AI can write the code.
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94% of marketers use AI, but only 3% of executives see a clear ROI. Bug or feature?