AI News Archive: August 21, 2026 — Part 15
Sourced from 500+ daily AI sources, scored by relevance.
- SiteLift
The fully autonomous SEO & AI growth engine.
- BarBrain
Create balanced cocktail recipes instantly with AI mixology
- PulseGuard AI
24/7Cloud Uptime & Instant AI Root-Cause Fixes
- SimplComIA
IA used to help people every day
- RxRobin
Intelligent Medical Assistant
- Codehoomer AI
AI engineering partner that reasons across your whole repo
- BuiltBy
Show what you have built
- 电商出图吧
从商品原图到整套电商视觉的 AI 工作台
- Channel Engage
AI partner enablement with approved messaging and deal flow.
- TwinLabs
Ideas Into Intelligent Software.
- InfiBis
AI-Powered ERP & Smart GST Billing for MSMEs
- Bestie
Turn anything you’re learning into a visual explanation
- Magento 2 ChatGPT AI Extension
Generate Magento product content faster with AI
- Axiom Docs
The documentation system for AI products, built in Framer
- Privacy Scribe
100% Offline AI Voice Dictation for Windows
- CommentLink
Turn Comments Into Conversations
- TuMango
Let our bots cut your bills
- Voidwear
Ghost Mannequin Photos That Show the Fit
- Stratezik AEO Tracker
Check your website AI Readiness
- SDR Motion
AI-powered pre-call research and scripts for SDR teams.
- FilmLune
Discover reusable prompts for AI image and video creation
- RateSelf
Your AI Assistant in Dating Apps - More Matches and Likes
- GPTCLEANUP
Clean Smarter. Write Better.
- Sellixy
Upload a photo, get marketplace-ready product images
- Script to Voice Generator - Kokoro TTS
Turn scripts into fully voiced audio—local, offline,
- MedCare MSO
AI medical scribe
- AI PDF Reader & Speech
AI PDF Reader & Speech
- RefundPe
The AI that fights for your money and gets your refunds back
- DigiBouquet
helps users design personalized virtual flower
- https://app.clearception.ai
See everything. Ask anything. Do more.
- AetherGrid
Open-source AI workload orchestrator, lease-based execution
- CLEOPATRA
AI business operations platform source code
- SutraAI
Give every AI the context you choose.
- Estima8
Estima8 is the AI quoting agent for print shops.
- Apple is reportedly cutting hundreds of jobs from Siri, Vision Pro teams
Apple has admitted that some roles are being impacted as it shifts its focus away from certain initiatives.
- Apple cuts more than 200 jobs across Siri and Vision Pro
Apple is cutting more than 200 jobs, roughly 100 from the Vision Pro organisation and 100 from Siri and software teams, largely shutting the headset’s gaming unit. The company says it is realigning teams and will create new roles. Apple is cutting more than 200 jobs across the teams that build Siri and the Vision […] This story continues at The Next Web
- Apple is laying off staffers working on the Vision Pro and Siri
Apple is laying off staff on the Siri and the Vision Pro teams, according to Bloomberg. The cuts include "largely shutting down" a Vision Pro gaming team and "reducing the size" of the team that makes Vision Pro immersive content, the publication says. More than 200 jobs were cut. Apple said in a statement to […]
- Waymo doubles spending on lobbying in robotaxi battle with Uber
Alphabet-owned company is seeking to persuade US regulators to clear a path for fully autonomous taxi services.
- Slack brings AI coding agents into shared team channels with Slack Code
Slack brings AI coding agents into shared team channels with Slack Code
- Slack wants to drag AI coding out of the terminal and into the group chat
Slack wants to drag AI coding out of the terminal and into the group chat. The Salesforce-owned messaging platform today announced Slack Code , a new product that embeds AI coding agents — including Anthropic's Claude Code , Cognition's Devin , GitHub Copilot , and Vercel's agent — directly into dedicated Slack channels where entire teams can watch, steer, review, and ship software together. Slack Code is available on any Slack plan at launch, though customers need their own access to the partner agents. The pitch is deceptively simple: today, most work with AI coding agents happens between one person and one agent, invisible to everyone else. Slack Code makes that work " multiplayer ." When someone tags a coding agent from any conversation, the agent spins up a project-specific code channel, does the work in the open — complete with code diffs, live previews, and a running plan visible in dedicated tabs — and archives the channel when the job is done, leaving behind a searchable audit trail. "One of the things I love about this is that code is no longer the bottleneck," Rob Seaman, Slack's interim CEO, said in a press briefing ahead of the launch. "Ideas, taste, judgment, craft — those are the things that are the bottleneck, and you've effectively extended the population that can contribute ideas, taste, judgment, and craft to anybody that exists in your Slack." It is a consequential launch for Slack, and a revealing one for the broader enterprise AI market. The AI coding boom has so far been a story of individual productivity — a developer alone with Claude Code or OpenAI's Codex in a terminal window. Slack is betting that the next chapter belongs to whoever owns the collaborative layer around those agents. And it is making that bet at a moment when its parent company badly needs the story to land. How Slack Code channels put AI coding agents to work in the open In the interview, which also included executives from Cognition, Slack leaders described a workflow that looks less like pair programming and more like a newsroom. Jeff Wang, president of new enterprise at Cognition — maker of the Devin coding agent — walked through a live demonstration: someone reports a broken feature in an engineering channel, Devin acknowledges it with an emoji, replies in the thread, investigates, and opens a pull request. "It even knows the code owner, so you can see it tagged Theo into this as well," Wang said. "Every time Devin is doing something like this, it does have its own computer. So here, it's actually using Chrome and the DevTools to test if the feature is working correctly." From there, the work migrates into a dedicated code channel where anyone — an engineer, a product manager, a designer — can jump in. In Wang's demo, a designer dropped a Figma file into the channel mid-task, and the agent incorporated it without breaking stride. The agent finished by posting the code changes alongside screenshots and a recorded demo proving the feature worked. That verification loop is central to the pitch: cloud-based agents, unlike agents running on a developer's laptop, can generate an auditable record that the work is actually correct. "Scaling things, auditing things, giving it to everybody — that is much easier with these cloud agents form factor than it is with local agents," Wang said. The launch reaches beyond code channels, too. Slack is shipping a broader rework of how agents live in the product: agent DMs that behave like conversations with a colleague, a new Agents tab that gives every agent session a home base with live status and a stop button, and an "Add to Slack" flow that lets teams deploy agents from platforms including Lovable , n8n , OpenAI , LangChain , and Airtable in a few clicks, with OAuth and configuration automated. Why Slack says writing code is no longer the bottleneck in software development The strategic argument underneath Slack Code is that AI has inverted the economics of software development. Writing code used to be the scarce, expensive step. Now, Slack's executives argue, it is the cheap one — and the constraint has moved upstream, to human judgment. "One of the things I love about this is that code is no longer the bottleneck," Seaman said in the press briefing. "Ideas, taste, judgment, craft — those are the things that are the bottleneck, and you've effectively extended the population that can contribute ideas, taste, judgment, and craft to anybody that exists in your Slack." Cognition offered internal numbers to back up the velocity claim. "We've seen our internal merged PR count go up 10x in the last few months, versus our headcount has only gone up like 40 percent," Wang said, describing a workflow where engineers fire off a Devin task, move to something else, and launch another — "soon you have everybody working on like dozens of agents at a time." The pattern extends well beyond engineers, Wang said. "Believe it or not, a lot of our bugs are reported by our sales team. They report it in Slack, and then someone who's technical applies them to fix the bug." Seaman seized on that example as the whole thesis in miniature: "So much of that stuff never even made its way to a product manager into a backlog because the communication vehicles weren't there, the motivation wasn't there, the knowledge that it could actually be fixed so quick wasn't there — and we've effectively knocked all of that down." Wang went further, sketching where he believes this ends up. Toil work — "fixing bugs, fixing CI/CD, or fixing vulnerabilities, all these things engineers probably don't want to do — we think will be automated away," he said. What remains is the work that "requires creativity, planning, business logic." He added a prediction that will make some engineering leaders uneasy: while a human still gates every merge today, "I suspect maybe in the next year it's just going to go through automatically." Can working in public solve the AI slop problem? The obvious objection to democratizing software creation is quality. If anyone in a company can summon a coding agent, does an enterprise drown in what the industry has taken to calling "AI slop" — plausible-looking but poorly conceived output generated at scale by inexperienced users? Slack's executives argue, somewhat counterintuitively, that visibility is the antidote rather than the accelerant. "The multiplayer part is a guard against that, actually, because people can see your work, people can comment on your work," said Katie Steigman, Slack's VP of product. She contrasted it with the status quo: "If I'm doing God knows what in terminal with an agent, versus being able to do it in a place where people can see my intent and actually change and shape my work — or slap my hand and tell me that's slop, because that's real." Steigman, a product manager rather than an engineer, described her own practice as a template. "When I put PRs up as a product person, I almost always tag in an engineer from my team. I don't just send a PR and ask for an approval," she said. "Almost every time, an engineer will say something like, 'Come on, you can make that a little bit tighter,' or they'll actually give it some specific technical guidance, and the agent will take one more rev and produce code that has been touched by an engineer to a certain extent." Seaman framed the argument in grander terms: "I think the moral arc of multiplayer AI bends towards higher quality and less duplication." He pointed to Shopify , where he said CEO Tobi Lütke has written about restricting agentic coding to public channels precisely because it "immediately disseminates every single thing that's happening in the company" and levels the playing field. Still, the skeptics' case has data behind it. Gartner predicted last year that more than 40 percent of agentic AI projects will be canceled by the end of 2027, citing escalating costs and unclear business value. And McKinsey's most recent State of AI survey found that while 62 percent of organizations are at least experimenting with AI agents, only about a third have begun scaling AI at all, and just 39 percent report any bottom-line impact. The gap between agent enthusiasm and agent value remains the defining feature of the market Slack is selling into. Inside Slack Code's security model: no god mode, no new identities For enterprise buyers, the most consequential design decision in Slack Code may be its permissions model. Asked directly whether agents in code channels could leak access across teams — a finance repo visible to legal, say — Seaman was emphatic that agents inherit the permissions of the human who invokes them, and nothing more. "Everything is done on behalf of the user, using the user's ACLs, both in Slack and in the systems that they're connecting to," he said. "There's no god permissions or bot-level permissions... Within Slack, the agent has access to information that the user has access to, and access to the channels that it's been added to." Steigman added that when an agent spins up a code channel, "the only thing that agent gets from the code channel is the context of the conversation" that triggered it. On the execution side, Wang said Devin runs in isolated sandboxes with "minimum viable access" — including an optional mode with no internet access at all. "You've heard all these stories about the agent escaping and causing havoc," he acknowledged, "but we have different security configurations." This "agents as extensions of existing users" model is a genuine differentiator against standalone agent platforms, which typically force IT departments to provision new service identities and manage a patchwork of one-off permissions. It also answers the shadow-IT question that has dogged agentic tools: because agents produce standard pull requests into GitHub, existing release gates and review processes still apply. "It reduces that barrier upfront to get that initial PR up," Steigman said. "Then the due diligence still happens in GitHub." What Slack Code means for Salesforce's high-stakes AI turnaround Slack Code arrives amid a turbulent stretch for its parent company. Salesforce shares fell roughly 18 percent over the year through January, badly lagging the Nasdaq, as Wall Street questioned whether AI would erode demand for traditional enterprise software. In December, OpenAI hired away Slack CEO Denise Dresser as its chief revenue officer, elevating Seaman — then Slack's product chief — to interim CEO. Salesforce has responded by racing to make Slack the AI front door for work. In January it shipped a rebuilt Slackbot powered by Anthropic's Claude , which the companies said became the fastest-adopted feature in the company's 27-year history. Slack Code extends that strategy from answering questions to producing artifacts: not just messages, but working code, prototypes, and documents generated inside Slack itself. There is also a notable strategic reversal embedded in today's news. In mid-2025, Reuters reported that Salesforce had moved to block rival AI firms from accessing Slack data — a defensive crouch. Today's announcement, by contrast, positions Slack as an open platform courting exactly those AI companies as partners, with plans to open the code channel APIs to any developer. Software engineering, the company says, is just the first use case; marketing campaigns and legal document reviews in dedicated agent channels are next. The calculus appears to have shifted from protecting Slack's data to making Slack indispensable as the venue where agents — anyone's agents — do their work. Partners are, unsurprisingly, saying the right things. "A whole team can gather in one code channel, watch the agent work, steer it together, and ship a preview," said Vercel CTO Malte Ubl. GitHub chief product officer Mario Rodriguez called Slack "a strategic part of a broader GitHub promise: humans set direction, agents close the loop." The future of AI coding: multiplayer channels and single-player terminals will coexist None of Slack's executives claim the terminal is dead. Asked whether tools like Claude Code and Codex become obsolete, Seaman predicted a division of labor. "The overwhelming majority of the work is actually going to happen in these multiplayer environments," he said. "But there's going to be deep, immersive, intensive, single-player thought work that's going to happen in terminals." An engineer rethinking a codebase's architecture goes heads-down with an agent; a sales rep flagging a broken button gets a fix in a channel everyone can see. The trust curve, Seaman suggested, will look familiar to anyone who watched teams adopt earlier waves of automation. "People are going to open these things at the beginning" — reading every diff, every thinking step — "and then build trust in the system and open it less and less over time." That is the wager, and it is bigger than a product launch. McKinsey's research shows the organizations capturing real value from AI are the ones that redesign workflows around it rather than bolting it onto old processes — and Slack Code is, at bottom, a workflow redesign packaged as a feature, an attempt to make the team rather than the individual the unit of AI adoption. If it works, the company that once changed where colleagues talk will have changed where software gets made. If it doesn't, all that transparency may just mean everyone gets to watch the slop pile up together. Either way, the era of the lone developer whispering to an agent in a private tab is ending. As Wang put it: "The bottlenecks have shifted." The question Slack Code will answer is whether the crowd makes them smaller — or just louder.
- Salesforce wants to move AI coding into a shared workspace with Slack Code
Salesforce wants to move AI coding into a shared workspace with Slack Code InfoWorld
- New ‘Slack Code’ turns AI coding into a team activity
With the launch of “Slack Code” channels, Slack this week introduced a new way for developers and non-tech staff to work collaboratively with coding agents . While Slack already integrates with several coding agents , developers have to interact with them independently to get work done. The aim of Slack Code is to make agents available to multiple coworkers in shared, project-based “code channels.” “We built code channels to be this multi-player AI experience and bring more development into Slack,” said Sateja Parulekar, vice president of product marketing at Slack. “It’s not just engineers and product managers who are working with the coding agents; it’s the marketers, the product designers who are now able to interact with a coding agent in a safe, governed environment.” Slack code channels are intended for one-off coding sessions and projects — building a new application feature, updating a web page, or fixing a bug, for example. When the coding agent is tagged in a Slack channel or DM with a request, it automatically creates a new code channel, adds links to required documents, and invites relevant participants. The code channel functions just like a normal Slack channel, with participants able to send messages and files as usual, while also letting them interact with a coding agent and track outputs via the channel’s “session artifacts.” These artifacts include “code diffs” that highlight changes to code made by the agent, as well as Slack “canvas” documents and live HTML that displays prototypes and previews created by the agent. All participants can use natural language to direct the agent, making suggestions and signing-off on outputs, for instance. Any updates are then highlighted in the original Slack channel. And when a task or project is complete, the code channel is automatically archived. Slack Code channels can also be customized — Slack admins can create guardrails to prevent non-technical workers from shipping code without engineering review, for example. Code channels adhere to Slack’s existing security and permissions model, the company said, with agents able to access conversations and data based on controls set for a Slack workspace. At launch, four agents integrate with Slack Code — Claude Code, Devin, GitHub Copilot, and Vercel — though Slack intends to expand the list of options over time. Slack Code is available at no extra cost on all Slack subscriptions. “Slack Code closes the gap between where work gets done and where code gets written with dedicated spaces built for output along project-based channels right in Slack,” said Wayne Kurtzman, research vice president at IDC. “This furthers the Salesforce goal of making work more seamless and multi-player within the Slack environment, regardless of the other applications the business is using. “While Slack Code may seem early to market for some companies, others are leveraging the first-mover advantage.” While software development and coordination work “has happened in Slack forever,” according to Will McKeon-White, senior analyst at Forrester, the new features make it “easier to just stay in Slack only and [open] up who is involved with the actual code creation.” For IT staffers who enable Slack Code, the immediate consideration involves permissions, he said — “a persistent challenge for anything multiplayer.” McKeon-White cites various approaches: “…Some inherit user permissions based on task, some have persistent permissions with different ‘invoking’ permissions for users, some inherit the permissions of the room. Each has flaws.” The longer-term challenge, he said, is around multi-agent collaboration. “Multi-agent collab today in successful environments isn’t very dynamic,” said McKeon-White. “Having true dynamic agents cooperating can create extremely interesting emergent behavior,” he said, pointing to recent Anthropic research on the topic. While Slack Code is aimed at software development-related tasks, Slack also envisages a similar cross-functional, collaborative approach to AI agent interactions applied to a wider variety of purposes: marketing campaigns, for instance, or legal document reviews. “That might not involve code per se, but it does involve a very detailed review of a document and tracking changes and a preview of what’s going to be sent out to the customer,” said Parulekar. “In the future, we see this extending to a lot of different teams and use cases for technical and non-technical users.” Other features announced Thursday include “agent DMs” that allow for individual interactions with an agent and a new “agents tab” where users can view existing agent conversations. Parulekar said Slack Code feeds into a wider Slack strategy centered on a “multi-player experience” for human workers and AI agents. This includes the recent announcement of Claude Tag , which makes Anthropic’s agent available to teams. “Whether it’s the user experience that we’re evolving — like the agent tab, or coding channels where you can plan, code, test, and ship inside of Slack — it’s all part of that bigger vision of making Slack a great home for agents and furthering that vision of multiplayer AI,” she said.
- AI coding gets a shared workspace with Slack Code
Slack has introduced Slack Code, a dedicated workspace for teams to collaborate with AI coding agents on software development. Code channels bring coding work into Slack, allowing developers and other […] The post AI coding gets a shared workspace with Slack Code appeared first on Express Computer .
- Wall Street Struggles to Absorb AI’s Debt Boom
Broadcom is lining up another massive bet on AI. Bloomberg has learned the chipmaker is in talks to raise more than $60 billion in debt to help Anthropic and others secure chips and computing power. The deal highlights a bigger concern hanging over the AI trade: the cost of funding it all. Erica Klauer, Science and Technology Partners founder and CIO, discusses concerns around circular financing and why the AI buildout is so challenging. She joins Ed Ludlow on "Bloomberg Tech." (Source: Bloomberg)
- America's capital crunch: Soaring debt collides with AI spending spree
America is caught in a historic capital squeeze: On one side: Trillions Washington must borrow to pay for the past . On the other: Trillions the economy needs to build the future . Why it matters: The next president will inherit a fiscal reckoning decades in the making. The price it exacts — on taxes, benefits, borrowing and investment — could shape America's prosperity and power for generations. Zoom in: President Trump said in 2016 that he could eliminate what was then roughly $19 trillion in national debt within eight years. On Tuesday, the debt crossed $40 trillion, after growing by $3 trillion in the past year alone. About $32 trillion is owed to investors and other outside holders. The rest is debt the government owes to its own accounts, including Social Security and other federal trust funds. Treasury must refinance $9.7 trillion in debt coming due this fiscal year while covering a deficit the Congressional Budget Office now projects at roughly $2.1 trillion. That creates a punishing cycle: Old debt comes due, Washington replaces it with more expensive debt, and the resulting interest bill feeds future deficits. CBO projects annual deficits will average $2.4 trillion through 2036, pushing debt held by the public to 120% of GDP — above the record set after World War II. The U.S. has already spent $963 billion on interest in the first 10 months of this fiscal year, $200 billion more than it spent on the military over the same period. Data: CBO; Chart: Sara Wise/Axios Zoom out: For years, Silicon Valley's AI buildout was financed almost entirely with cash. Now Big Tech is becoming one of the biggest new forces in global debt markets. Bond sales by the "hyperscalers" building AI infrastructure are on pace to roughly double in 2026. Goldman Sachs projects debt will fund more than a third of their AI spending by 2027. Nvidia is working with BlackRock, Goldman Sachs, KKR and other Wall Street giants on plans to marshal more than $500 billion for AI infrastructure. Stunning stat: Nine major tech companies have already spent roughly $600 billion on capital projects over the past year. A Wall Street Journal analysis found they have another $3 trillion in future commitments, mostly tied to AI, that aren't yet reflected on their balance sheets. The big picture: America's debt burden is approaching the point where it starts reshaping household finances, presidential politics and the country's economic choices. Long-term Treasury yields have climbed to their highest levels since 2007, raising borrowing costs across the economy — from mortgages to business loans — and making Washington's own debt more expensive to refinance. Social Security's retirement trust fund is projected to run dry in late 2032, during the final months of the next president's first term. Medicare's hospital trust fund follows in the second quarter of 2033. Between the lines: Trump and Elon Musk promised to break Washington's addiction to debt without forcing Americans to swallow painful sacrifices. Musk launched DOGE with ambitions of cutting as much as $2 trillion from federal spending. Its final public tally claimed just $215 billion in savings — barely a tenth of that goal. A federal audit released this month found billions in unsupported or inaccurate savings claims, including $27.4 billion tied to contracts that were still active. What to watch: America's fiscal options are narrowing as its political ambitions expand. On the left, democratic socialism and economic populism are surging, pairing promises of cheaper housing, health care and child care with calls for higher taxes on the wealthy. On the right, the Trump-era GOP has protected Social Security and Medicare politically while pursuing tax cuts and higher defense spending, including Trump's push for a $1.5 trillion Pentagon budget . The bottom line: Few problems loom larger over America's future than its colossal debt burden. Yet few are treated with less urgency by the politicians who will have to confront it.
- US corporate AI debt surge tests investor limits as fatigue emerges
While fund managers remain comfortable with the credit quality of companies such as Amazon and Alphabet, Google's parent company, they are increasingly demanding higher yields to accommodate the flood of issuance. This has raised concerns that a tipping point could emerge if AI spending continues to escalate.
- GPT-5.6 Sol drives OpenAI's revenue surge as it regains ground on Anthropic
Since GPT-5.6 Sol launched in early July, OpenAI says revenue is up 35 percent this quarter, with enterprise revenue growing more than 50 percent. Ramp data shows OpenAI outpacing Anthropic in business API spending for the first time after Anthropic had overtaken OpenAI in quarterly revenue. The article GPT-5.6 Sol drives OpenAI's revenue surge as it regains ground on Anthropic appeared first on The Decoder .
- GPT-5.6 Sol is now 50% off a lower price
OpenAI lowered list pricing for GPT-5.6 Sol , and the 50% AI Gateway discount now applies to the new, lower price through September 18. Input drops 20%, output drops a third. The discount applies on every OpenAI service tier: Service tier You pay now (input / output) New list price (input / output) You paid before (input / output) Default $2.00 / $10.00 $4.00 / $20.00 $2.50 / $15.00 Flex $1.00 / $5.00 $2.00 / $10.00 $1.25 / $7.50 Priority (fast mode) $4.00 / $20.00 $8.00 / $40.00 $5.00 / $30.00 Rates are per million tokens for requests up to 272K tokens. Cached tokens, cache writes, long-context requests above 272K, and the US regional rates all move by the same proportion. See the pricing page for all model rates. The model ID is unchanged, so requests you already send bill at the new price automatically. BYOK requests bill at your own rate with OpenAI. To use Sol in a coding agent, run vercel ai-gateway coding-agents setup to connect your agents to AI Gateway, then select openai/gpt-5.6-sol in the agent's model settings. See the coding agents guide for setup details. Try it in the playground , or browse every language model on the AI Gateway. Read more
- OpenAI cuts developer pricing for frontier GPT-5.6 Sol model by more than 20%
OpenAI cuts developer pricing for frontier GPT-5.6 Sol model by more than 20%
- China’s humanoid robot boom and industrial challenges
China’s humanoid robot boom and industrial challenges The Straits Times