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Baseten's API for GLM-5.2 has peak speeds of 280 tokens per second and average speeds of around 100 tokens per second. It has more than double the performance of the launch-day API. The company has also built a Fast version of the API, which is focused on reducing latency for coding and agents. It plans to roll out another improvement to its speculative decoding algorithm soon that will further optimize the performance of GLM-5.2.
The problem with great type-system power is that it requires great proof effort. Doing proofs can be fun, but they take a lot of time. It can take hours of effort to discover that what you were trying to prove was false. This overhead has made programming in dependently typed languages extremely niche. It has also spurred people to try and automate it away. LLMs promise to be an extremely capable form of proof automation.
Prompt caching makes agents more economic, but this is quite fragile. A changed tool definition, a model switch, or a provider routing decision can turn a cheap incremental request into a full replay of the context. Cache behavior affects latency, cost, tool design, session design, and even which product features should be made available. This post looks at what the cache is, how it works, and common reasons for worse cache performance.
Claude 5 models now prioritize judgment over strict rule-based context engineering, with prompts shifting from rigid guidelines to adaptable strategies. Progressive disclosure helps optimize context usage by loading necessary information on demand, while simple tool descriptions replace repetitive instructions. Claude auto-saves relevant memories and utilizes rich references like HTML artifacts for handling complex tasks.
SANA-Video 2.0 combined linear attention with periodic softmax layers to generate videos up to 720p on a single GPU. Its 5B and 14B models retained competitive quality while substantially reducing latency for long, high-resolution generation.
celeris-1 is a general-purpose language model that delivers near-GPT-5 level intelligence with 15x faster response times. It uses a new inference architecture that uses diffusion techniques, unlocking dramatically better speed while maintaining frontier-level intelligence. The model delivers p50 response latency of 157ms and a throughput of 1,280 tokens per second. A link to a post on how the model was built along with full benchmarks is available.
AI agents can work through loops to complete complex tasks. Domains that work around problems with verifiable answers are susceptible to these kinds of loops. This is a new form of brute force. It is like having a million scientists working in a million labs, all taking swings at the same thing. While AI may not be smarter than humans, it is faster. Being fast enough might make up for the difference in intelligence.
Nvidia calls for US government policies to support open-weight AI models, arguing this fosters innovation and enhances AI leadership. The company emphasizes how open weights allow researchers to build on existing models, speeding up advancements. Nvidia's push aligns with broader industry efforts to encourage transparency and collaboration in AI development.
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OpenRouter Classifiers allow developers to tag inference in their workspaces by task type, department, agent complexity, or anything else.
The Legora BAR evaluates AI models on real legal cases within a practical environment, unlike traditional benchmarks with synthetic setups.
NVIDIA ModelExpress accelerates model weight distribution by using P2P RDMA for direct GPU-to-GPU transfers, reducing startup times significantly.
Nanbeige4.2-3B is a compact, dense model intended to make capable agentic behavior practical on consumer and workstation hardware, and Laguna S 2.1 is an 118-billion-parameter Mixture-of-Experts model that uses sparse access to a much larger pool of learned parameters.
Amazon is overhauling Prime Video's home screen through an internal project called Lighthouse, personally driven by Jeff Bezos, replacing the static tile grid with AI-generated, personalized recommendations. The redesign follows a tense meeting last fall where Bezos pushed executives to lean harder into AI. It remains unclear whether AI-driven rankings will genuinely reduce paid placement bias or simply shift it into the algorithm, leaving real benefits to viewers uncertain until testing expands beyond the current small user group.
Hyundai Motor Group has opened UX Studio Shanghai, a dedicated user experience research hub in Jing'an district, completing its four-city network alongside Seoul, Frankfurt, and Irvine facilities. The three-story studio splits into a public Open Lab, with Explorer, Test, and Archive zones, and an invite-only Advanced Lab housing a simulation platform for concept-to-validation co-development.
WhatsApp is testing redesigned chat bubbles on iOS that feature significantly rounder, softer corners, bringing them closer to iMessage and better aligning with its recent Liquid Glass redesign. The update also removes the green outlines around photos, videos, GIFs, and link previews for a cleaner, more integrated appearance. The changes are currently limited to select TestFlight users, with no confirmed date for a wider rollout.
iOS 27 introduces a major AI-powered Siri upgrade that addresses three key weaknesses: world knowledge, conversational interactions, and consistency across Apple devices. Siri can now answer broad questions, maintain conversations with follow-ups and chat history, and provide the same capabilities across iPhone, Mac, Apple Watch, iPad, and, eventually, Apple TV and HomePod. Deep integration with Apple apps also enables personalized assistance based on messages, notes, and email, potentially giving Siri a significant advantage for everyday Apple users.
Building small side projects is one of the fastest ways for UX professionals to learn how AI is changing software development, with tools like Claude Code, Codex, and Cursor dramatically lowering the technical, time, and cost barriers to creating real products. Rather than relying on highly abstracted tools like Lovable, working closer to the actual development process—doing discovery and design, learning concepts such as version control, and asking AI to explain unfamiliar technology—builds much deeper practical knowledge. The key is to build with AI rather than have AI build everything for you, gaining technical fluency and end-to-end product-building skills through hands-on experience.
A visit to an art school studio shows how painting habits mirror the judgment senior designers build over time. Design differs from art in serving someone else's outcome, yet deliberate practice—training the eye as art students do—builds taste no tool can replace. As prompts turn ideas into finished apps within days, skipping the slow, layer-by-layer deconstruction that art students practice may cost designers the deeper judgment such practice builds.
Chart your design system across six axes of maturity: foundations, documentation, governance, adoption, measurement, and AI readiness.
VideoDB turns files, live streams, and camera feeds into persistent, searchable context that AI applications and agents can retrieve and act on.
A design team's rollout of Claude Code in February revealed pressure to appear competent before actually mastering the tool, echoing a similar pattern at Slack. Drawing on researchers and practitioners, the piece argues AI adoption should be treated as reversible experimentation built on candor, shared vocabulary, and coordinated workflow changes across design and engineering. Survey data showing most designers feel overwhelmed and pressured to do more underscores the case for making uncertainty visible rather than hidden.
A UX reviewer argues against using interruption pages, a GOV.UK Design System pattern meant to pause users with warnings mid-journey. Interruption pages offer multiple actions, use unconventional button labels, and look like dismissible banners rather than part of the form flow. A standard question with radio buttons is recommended instead, since it forces conscious decisions without needing a visually distinct screen.
AI agents are eliminating the traditional designer-developer handoff, letting teams build live together in real time instead of manually translating Figma files into code.
Coca-Cola's newly overhauled brand identity, designed by JKR, gives greater prominence to the "Better With" serif typeface, created by Brody Associates in 2023 for a holiday campaign.
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An AI IDE can make engineers ship faster. That does not mean the team is getting better. NVIDIA saw 3x more committed code across 30,000 developers without more bugs, but the companies closest to that result had rebuilt the workflow around GitHub, Linear, review, and testing. Another dataset is the warning: epics finished 66% faster while bugs per developer rose 54%. If your AI dashboard only shows pull requests, it is probably hiding half the story.
A software factory is a coding pipeline where agents take a spec and return working code with little or no human review. The pitch borrows from lights-out manufacturing: the line runs while nobody is on the floor. HumanLayer tried it in July 2025. Three months later, a production bug dropped the team into code nobody had been reading, and the cofounder spent two weeks rewriting the core patterns. Agents can run the line. Someone still has to understand the factory well enough to know when it is drifting.
Duolingo did not sell better software to schools. Coinbase did not sell better ledgers to banks. Both moved something the gatekeeper controlled directly to the customer. AI founders now face the same choice. An AI doctor that can prescribe changes the market more than software that helps a doctor type notes. Software that runs a factory changes more than a dashboard sold to its manager. If your customer still needs the same gatekeeper after buying the product, you may be making the old market faster rather than building a new one.
Most founders cut onboarding. Cal AI made users do more of it, then built a multimillion-dollar subscription business. Before the price appeared, users entered their goals, body type, habits, and timeline, then watched the app assemble a plan. By the time they saw the paywall, it felt less like buying another calorie tracker and more like walking away from a plan made for them. That only works when the pain is real: every question must sharpen the product or increase commitment.
What does a healthy B2B pipeline actually look like? One founder with real revenue and Fortune 500 customers discovered that most of his pipeline was fake. This is the scorecard he wished he had. For a $100K+ product, each seller should book three first meetings a week. 60% should show real buying behavior, half of those should close within 90 days, and 95% of customers should reach the first retention milestone within a month. You can disagree with the numbers. At least they are hard to explain away.
This post shares how the team at Clay uses AI in their day-to-day. It covers how to generate on-brand decks from a single prompt, spin up custom apps for each customer, and clear the Salesforce chores nobody wants to touch. The post walks through Clay's full AI sales stack, the exact tools used, and 10 concrete ways the team puts AI to work.
The GitHub Copilot app is an interface for agent-driven development built natively on GitHub. It allows developers to move from issue to merge all in one app. Developers can run multiple sessions across every area of work with parallel workflows fully in view. The app can be extended with MCP servers, plugins, and skills.
Claude Opus 5 is now available on all platforms, priced at $5 per million input tokens and $25 per million output tokens. A Fast mode that runs around 2.5 times the default speed is available at twice the base price. Anthropic has also introduced mid-conversation tool changes on the Claude Platform and automatic fallbacks on the API. Details about what has been improved in Claude Opus 5 are available in the article.
After reviewing 15 of her own agent sessions, NextView's Melody Koh found that the agent was not wasting her time on the work. It was wasting it on corrections. The same mistakes kept returning because she had never told the model what "good" meant for quality or positioning. Her fix was to make those judgment calls upfront, let the agent handle the checkable middle, and review once at the end. If you correct the same mistake twice, it belongs in the instructions.
A junior engineer does not become senior by doing senior work. They get there by doing the routine work first: reading the codebase, seeing exceptions, and learning what "good" looks like. Coding agents can remove that apprenticeship while making output look better in the short term. The useful question is not "which jobs can AI replace?" It is "which capabilities disappear with the task?" Before automating work, ask whether it was also building context, taste, or the person who would catch the weird case later.
Sometimes it is wiser to eliminate the defaults within yourself.
Service with a Software - private tools that never get sold, built to make one service impossible to compete with - is the strongest position left for independent builders.
This fund now looks for founders who are good at StarCraft because they already know how to allocate scarce resources, sequence parallel work, and intervene before one bad unit loses the map.
Winning teams are quick to admit what they don't know, and quicker to help each other fill those gaps.
Patience is a form of arbitrage.
Companies are cutting AI costs by mixing models instead of relying solely on premium providers like OpenAI and Anthropic. Businesses are using cheaper open-weight models for routine tasks while reserving advanced models for complex work. Cursor found a hybrid approach reduced a browser-building experiment from $10K to $1.3K, showing how companies are optimizing AI spending with flexible model choices.
Microinfluencers have become a more cost-effective advertising channel because loyal niche audiences often deliver stronger engagement at a lower price than large creators. Microinfluencers average a 3.2% engagement rate versus 1.1% for macroinfluencers. Brands now hire many smaller creators instead of a few large ones to get better returns from the same budget. The creator economy has grown to a projected $33B in 2025 as affiliate links, brand deals, and storefronts give creators multiple ways to earn revenue.
Build Meta lookalikes and Google Ads Customer Match audiences from CRM segments such as SQLs, opportunities, and closed customers instead of all form submissions. Use at least 100 seed records and aim for 1,000+ when possible. If you don't have enough closed customers, combine qualified stages to create a larger audience.
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