A free, practical session showing sales teams how to put AI to work in their daily routine, no technical background required. Hosted by Josh Sullivan, COO of Kiingo AI. We’ll cover how to:

• Clean up your pipeline without the busywork: flag stale deals and keep your CRM accurate automatically
• Walk into every meeting prepared, with an AI agent that scans your week ahead and researches who you’re meeting
• Follow up faster with personalized emails and instant call summaries
• Close smarter by spotting buying signals and prioritizing the deals most likely to move

Tuesday, June 16 • 10:00 AM PT / 12:00 PM CT / 1:00 PM ET
Save your spot →

• Anthropic shipped Claude Opus 4.8, its new flagship model, with a feature that splits a big task into hundreds of smaller jobs run in parallel, tunable “effort” controls that trade response speed against cost, and a roughly 4x drop (vs. 4.7) in the model glossing over flaws in its own code — at the same price as 4.7. The same week, it raised $65 billion at a ~$965 billion valuation, overtaking OpenAI as the world’s most valuable private AI company. (Anthropic, TechCrunch)

• OpenAI tuned GPT-5.5 Instant for shorter, less bullet-heavy answers and folded writing and coding “blocks” directly into chat responses. It also confirmed sunset dates inside ChatGPT: GPT-4.5 retires June 27 (30-day window); o3 retires August 26 (90-day window). API customers are unaffected. (OpenAI Release Notes)

• GitHub Copilot moved to usage-based billing across paid tiers, replacing the flat per-seat fee with “AI credits” that are metered by how much you actually use. The shift lands the same week Fortune reported that agentic systems can consume up to 1,000x more tokens than ordinary chatbot use, and that Uber’s CTO burned the company’s entire 2026 AI coding budget in four months. (GitHub Changelog, Fortune)

• Snowflake’s stock jumped roughly 36% — its best day on record — after a quarterly earnings beat (product revenue up 34%) that the company tied directly to enterprise AI demand on its platform. Snowflake also committed to spending $6B on AWS over five years to scale that capacity. The earnings, not the spend, are the clean signal that enterprise AI is producing real revenue, not just press releases. (Reuters via Yahoo Finance)

• Cognition, the maker of the autonomous coding tool Devin, raised more than $1 billion at a $25 billion pre-money valuation — more than double where it stood eight months ago, on roughly $492 million in annualized revenue. (TechCrunch, Bloomberg)

• HubSpot launched an Agent CLI that brings HubSpot data and actions into the agent environments teams already use — Claude Code, Claude Cowork, and Codex — to automate repetitive, bulk, and scheduled CRM work without a human in the loop. Aimed at marketing and sales teams that want lightweight automation against their CRM without commissioning a full custom build. (HubSpot Blog)

• Asana acquired StackAI, a no-code platform for building AI “agents” that carry out multi-step tasks across the tools a business already runs (CRM, ERP, and the like), for $75 million — its first acquisition in 18 years. A sign that the big work-management platforms want ordinary teams to automate workflows without hiring engineers to build them. (TechCrunch, Fortune)

• Microsoft used its Build 2026 conference to unveil seven of its own AI models, led by MAI-Thinking-1, its first reasoning model, built without relying on OpenAI’s technology and aimed at cutting developer costs and reducing its dependence on its longtime partner. Separately, NVIDIA’s GTC Taipei was headlined by Nemotron 3 Ultra (its largest freely downloadable model), Cosmos 3 for robotics, and an RTX Spark platform (Grace+Blackwell, 128GB unified memory) that runs large models locally on Windows PCs. (GeekWire, CNBC, NVIDIA)

• OpenAI’s frontier models and its Codex coding tool are now available to AWS customers, letting companies use them through the security, billing, and compliance setups they already have. OpenAI also said more than 5 million people now use Codex each week (a self-reported figure). One more sign the model makers are racing to meet enterprises inside the clouds they already pay for. (OpenAI, Amazon)

• Anthropic, the maker of Claude, confidentially filed draft IPO paperwork with the SEC, setting up one of the biggest tests yet of investor appetite for AI on the public markets. A successful listing would make it one of the most valuable AI firms to trade publicly. (Washington Post, CBS News)

• KPMG’s 2026 US CEO Outlook Pulse Survey of 100 US CEOs at companies with $500M+ revenue found 55% expect to increase hiring over the next year as a direct result of AI, while 36% expect no change. Only 9% of CEOs attribute targeted workforce reductions to AI specifically. 77% say GenAI may have been overhyped over the past year, but its impact over the next 5 to 10 years is likely to be underhyped. (KPMG, 2026)

• Bain & Company’s survey of 100+ global CFOs (half at companies with $5B+ revenue) found 83% plan to increase enterprise-wide AI spending by more than 15% over the next two years, and 42% plan to increase by more than 30%. The largest share of finance-function AI investment in the next 12 months is going to financial planning, analysis, and reporting. (Bain, April 13, 2026)

• Accenture’s Pulse of Change (3,650 C-suite executives and 3,350 workers across 20 countries and 20 industries, surveyed Nov-Dec 2025) found 79% of workers report positive learning experiences with AI training, and 32% now work regularly with AI agents. The opportunity ahead: only 40% feel fully prepared for the role changes coming. Accenture’s takeaway: training works best paired with clear role and workflow guidance. (Accenture, Pulse of Change 2026)

Our June 16 webinar covers putting AI to work across your whole sales day. Here's a smaller move to try before then — one most reps never think to make. You know you should prep for objections; almost nobody does, because imagining every angle a skeptical buyer will take is a chore.

So don't imagine it — make the AI be the buyer. Tell it who you're selling to and what you're pitching, and it hands you the exact pushback you'll get, what's really behind each one, and your best answer. Five minutes before a call, and you walk in having already heard the "no."

The Objection Drill
You're going to play a skeptical version of my prospect, then switch to being my sales coach.

Here's who I'm selling to and what I'm offering:
- Prospect: [role, company, industry, size]
- Where we are: [stage — after the demo, reviewing the proposal, gone quiet, etc.]
- What I'm pitching: [product/offer, and price if it's on the table]
- Optional: [paste my last email, pitch, or proposal]

Step 1 — As the prospect, list the top 5 objections or hesitations you'd realistically raise, ranked by how likely they are. For each, in one line, name what's really behind it — the underlying concern, not the surface words.

Step 2 — Now as my coach, for each objection give me my best response in 2-3 plain sentences (no hype), plus one question I could ask earlier in the conversation to defuse it before it ever comes up.

Return it as a table: Objection | What's Really Behind It | My Response | Pre-empting Question.

The morning of any real call, run it. When the first time a buyer raises an objection and you already have the answer ready, you'll wonder why you ever winged it.

The thing nobody warns you about with AI agents: the bottleneck isn’t the AI. It’s whether you’ll slow down for an hour up front to structure the work properly.

I finally tackled a project I’d been dodging for months. Dozens of moving pieces, the kind where one wrong click loses a file and you find out three weeks later. So I built it right: approval gates, a spreadsheet of every action before anything happened, a copy-then-verify-then-delete pattern so nothing could go missing. Hours, not days. And I was making every call. The AI just did the execution.

Here’s the part nobody talks about, and it’s the real reason this matters. Once you’ve built it carefully once, you can package it up and run it again. Different project, same pattern. The hour you spent designing it isn’t a cost. It’s a template. That’s where this starts to compound.

So if there’s something organizational you’ve been avoiding, don’t wait for a free week. Spend the hour, build the pattern, and you’ll be reusing it long after the first project is done.

Kiingo AI

The strategy decks keep stacking up. The pilots keep launching. The way the work actually gets done? Unchanged.

We help mid-market companies get past the planning and into implementation — starting with the two or three places where AI actually moves the needle.

Want to see what that could look like for your team? Get in touch.