In partnership with
How Your Ads Will Win in 2026
Great ads don’t happen by accident. And in a world flooded with AI-generated content, the difference between “nice idea” and “real impact” matters more than ever.
Join award-winning creative strategist Babak Behrad and Neurons CEO Thomas Z. Ramsøy for a practical, science-backed webinar on what actually drives performance in modern advertising.
They’ll break down how top campaigns earn attention, stick in your target’s memory, and build brands people remember.
You’ll see how to:
Apply neuroscience to creative decisions
Design branding moments that actually land
Make ads feel instantly relevant to real humans
In 2026, you have to earn attention. This webinar will show you exactly how to do it.
Morning Coffee: OpenAI Just Signed a $10 Billion Chip Deal—And It Wasn't With Nvidia. Yesterday, OpenAI announced a multi-year agreement with Cerebras Systems worth over $10 billion for 750 megawatts of computing power through 2028. This is the largest high-speed AI inference deployment in the world. And the chip supplier isn't Nvidia.
The thesis is straightforward: OpenAI is diversifying its compute stack. The company already has deals with Nvidia ($100B infrastructure commitment announced in September) and AMD (six gigawatts of GPU capacity). But Cerebras offers something different—wafer-scale processors that run inference workloads up to 15x faster than GPU-based systems. In testing, Cerebras hardware ran OpenAI's GPT-OSS-120B model at speeds that make real-time AI feel genuinely real-time.
Why this matters beyond the headlines: The AI infrastructure race is no longer a Nvidia monopoly story. It's a portfolio optimisation problem. OpenAI's compute strategy now explicitly matches "the right systems to the right workloads"—GPUs for training, specialised silicon for inference. As Cerebras CEO Andrew Feldman put it: "Just as broadband transformed the internet, real-time inference will transform AI."
For Cerebras, this is validation at scale. The company is in talks to raise another $1 billion at a $22 billion valuation (nearly 3x its September 2025 valuation) and is preparing to refile for a Q2 2026 IPO. For OpenAI, it's infrastructure groundwork for a potential trillion-dollar public debut.
The question: if the future of AI is real-time interaction at scale, who wins—the companies building models, or the companies building the silicon that makes those models fast enough to feel human?
GROWTH HACK
API Growth Hack to Increase Cross-Sell
Here's a growth lever hiding in plain sight: your API integrations are passive pipes when they could be active revenue channels.
The Play: Add a cross-product API event trigger so that when users complete a key action (finish onboarding, hit a usage milestone, unlock a feature), you trigger a tailored upsell call-to-action in partner products via API.
Example: User completes 100 API calls → Partner app surfaces: "Unlock Premium Analytics in [Your Product]"
Why This Works:
The timing is perfect. You're catching users at peak engagement—they've just accomplished something. Traditional cross-sell relies on email drip campaigns hitting cold inboxes. This hits warm users at the moment of success.
The Implementation Stack:
Event tracking: Segment or RudderStack (Free tier) Trigger logic: n8n or Zapier (Free–£25/mo) Partner API: Custom webhook (Free) A/B testing: LaunchDarkly (Free tier)
Step 1: Define Milestone Events
Pick 3–5 actions that signal high intent:
Onboarding completion
First successful API call
Usage threshold (100 calls, 1GB processed, etc.)
Feature unlock
Subscription renewal
Step 2: Build the Webhook
// Example event payload to partner API
{
"event": "milestone_reached",
"user_id": "usr_12345",
"milestone": "onboarding_complete",
"timestamp": "2026-01-15T09:30:00Z",
"context": {
"plan": "growth",
"usage_30d": 847,
"eligible_upsells": ["premium_analytics", "priority_support"]
},
"cta": {
"headline": "Unlock Premium Tools",
"link": "https://yourapp.com/upgrade?ref=partner_api"
}
}
Step 3: Partner Integration
Work with integration partners to surface your CTA in their UI. Offer reciprocal triggers—this becomes a two-way revenue channel.
The Monetisation Angle:
Revenue share: 15–25% of attributed conversions
Co-marketing: Joint case studies drive both brands
Stickiness: Users embedded in your ecosystem churn less
Every integration becomes a micro-cross-sell machine that surfaces the right offer at the right moment across your ecosystem.
DAILY STAT
75% of Enterprise Data Will Be Processed at the Edge by 2026
By next year, three-quarters of enterprise data will be generated and processed at the "edge"—on local devices and sensors rather than in centralised clouds. This creates a massive opportunity to serve customers with zero-latency personalisation.
Why This Matters:
The edge isn't just about speed. It's about trust. Sensitive data stays local. Customers get instant responses. And you're not paying cloud egress fees for every interaction.
The Technology Enabling This:
Businesses are deploying Edge AI—specifically Small Language Models (SLMs)—directly onto local hardware to analyse customer behaviour and environmental context in real time without the lag of remote servers.
Real-World Applications:
Smart kiosk: Offers personalised discount the moment a customer looks at a specific product
Retail analytics: Inventory sensors trigger restocking before shelves empty
Industrial IoT: Predictive maintenance catches failures before they happen
Healthcare devices: Real-time patient monitoring with instant alerts
What This Means for Builders:
Latency-sensitive apps → Deploy SLMs on-device Privacy-first products → Keep data local, process at edge Cost optimisation → Reduce cloud compute bills New revenue streams → Edge-as-a-service offerings
The Privacy Angle:
Edge processing keeps sensitive data off the public cloud. In a world where data privacy regulations are tightening globally, this isn't just a performance play—it's a compliance strategy.
Companies that master edge deployment will own the next decade of real-time, hyper-contextual customer experiences.
Source: Gartner Edge Computing Forecast 2025; IDC Edge Infrastructure Report
TOOL TIP
Claude Cowork — AI That Executes Work, Not Just Text
URL: claude.ai (Cowork features)
What it does: Claude Cowork is Anthropic's emerging AI-powered assistant built to handle everyday tasks and workflow execution. Unlike traditional chatbots that generate text and leave implementation to you, Cowork actually does the work—writing files, editing documents, running code, and completing multi-step tasks autonomously.
Pricing:
Free — £0 — Basic Cowork access, limited usage Pro — £16/month — Extended limits, priority access Team — £24/user/month — Collaboration features, admin controls Enterprise — Custom — SSO, advanced security, dedicated support
Who it's for:
Knowledge workers — Automate document creation, data analysis, report generation
Developers — Code execution, debugging, file manipulation without context switching
Creators — Newsletter production, content formatting, research synthesis
Operations teams — Process automation, data transformation, workflow execution
What makes it different:
Executes, doesn't just suggest — Creates actual files, runs real code, completes tasks end-to-end
Computer use capabilities — Interacts with tools like a human would
Context retention — Maintains understanding across complex, multi-step workflows
Artefact creation — Produces downloadable documents, spreadsheets, presentations
Use cases that work well:
Research synthesis: "Analyse these 10 articles and produce a summary report"
Document automation: "Create a formatted proposal from these notes"
Data processing: "Clean this CSV, add calculations, export to Excel"
Code tasks: "Build a Python script that does X, test it, fix any bugs"
Content production: "Format this newsletter draft with proper styling"
Limitations to know:
Complex real-time integrations may require external tools
Some tasks benefit from human review before final output
Learning curve for optimal prompting
Why it's breaking out:
The shift from "AI that chats" to "AI that works" is the next inflection point. Early adopters in tech communities are reporting significant productivity gains by delegating execution-heavy tasks. This represents the evolution from generative AI to agentic AI.
The bottom line: If you're spending hours on tasks that are mostly mechanical—formatting, data wrangling, document assembly—Cowork is the infrastructure layer that handles execution so you can focus on decisions.
TICKER WATCH
Opendoor Technologies (NASDAQ: OPEN) — $3.47 The PropTech Play Riding Housing Market Recovery
Current Price: ~$3.47 Market Cap: $2.4B 52-Week Range: $1.55 – $5.58 Revenue (TTM): $6.9B Gross Margin: ~7.5% Cash Position: $1.1B+
What they do: Opendoor is the leading iBuyer—they buy homes directly from sellers, make light renovations, and resell them. Think of it as "Carvana for houses." The model promises sellers speed and certainty; Opendoor promises investors a data-driven real estate arbitrage machine.
Why OPEN fits HackrLife: This isn't a traditional real estate play. It's a technology bet on whether AI-powered pricing models can consistently generate spreads in the housing market. The company has rebuilt its unit economics post-2022 housing correction, and recent momentum suggests the market is noticing.
The Thesis:
Opendoor's 2022–2023 was brutal. Rising rates crushed the housing market. The stock touched $1.55. But here's what changed:
Unit economics recovered: Contribution margin turned positive again
Inventory discipline: Holding periods shortened, reducing carrying costs
AI pricing refinement: Their models got smarter after stress-testing through the downturn
Housing market stabilisation: Transaction volumes rebounding
The stock is up significantly from its lows, but still trades at a fraction of its 2021 highs. The question is whether the operational improvements are durable.
The Catalysts:
Housing transaction volume recovery as rates stabilise
Expansion into new markets (currently 50+ metros)
Partnership announcements with builders and agents
Potential path to sustained profitability in 2026
The Risks (Be Clear-Eyed):
Interest rate sensitivity — Housing demand swings with mortgage rates Execution risk — Pricing model errors = inventory losses Competition — Zillow exited; others may enter Cash burn — Still not consistently profitable Macro exposure — Recession = housing freeze
Technical Indicators:
Recent volume: Elevated post-momentum
Trend: Recovery from December lows
Resistance: $4.50–$5.00 range
Position Sizing: This is a speculative play on housing recovery and PropTech execution. High reward potential comes with high volatility. The $1.1B cash position provides runway, but profitability timing remains uncertain. Size accordingly—not a core holding.
Not financial advice. Do your own research.
WORKFLOW
Automated New Customer Onboarding Hub
Setup time: 30 minutes | Weekly value: 5+ hours saved
Instead of manually processing new customers, this workflow automatically updates your systems, creates onboarding tasks, notifies your team, and segments users for future campaigns—all triggered the moment a payment succeeds.
The Architecture:
Trigger: New customer created in Stripe
↓
Action 1: Update CRM (HubSpot) contact record
↓
Action 2: Create personalised Trello card with onboarding tasks
↓
Action 3: Send internal Slack alert to ops/success team
↓
Action 4: Add user to segmentation list in Mailchimp (by plan)
↓
Outcome: Automated onboarding with notifications and segmented marketing
n8n Workflow (Import-Ready JSON)
{
"name": "New Customer Onboarding Hub",
"nodes": [
{
"parameters": {
"events": ["customer.created"],
"secret": "={{$env.STRIPE_WEBHOOK_SECRET}}"
},
"name": "Stripe Trigger",
"type": "n8n-nodes-base.stripeTrigger",
"position": [250, 300]
},
{
"parameters": {
"values": {
"string": [
{"name": "customer_email", "value": "={{$json.data.object.email}}"},
{"name": "customer_name", "value": "={{$json.data.object.name}}"},
{"name": "customer_id", "value": "={{$json.data.object.id}}"},
{"name": "plan_type", "value": "={{$json.data.object.metadata.plan || 'starter'}}"}
]
}
},
"name": "Extract Customer Data",
"type": "n8n-nodes-base.set",
"position": [450, 300]
},
{
"parameters": {
"resource": "contact",
"operation": "upsert",
"email": "={{$node['Extract Customer Data'].json.customer_email}}",
"additionalFields": {
"firstName": "={{$node['Extract Customer Data'].json.customer_name.split(' ')[0]}}",
"lastName": "={{$node['Extract Customer Data'].json.customer_name.split(' ').slice(1).join(' ')}}",
"properties": [
{"name": "stripe_customer_id", "value": "={{$node['Extract Customer Data'].json.customer_id}}"},
{"name": "plan_type", "value": "={{$node['Extract Customer Data'].json.plan_type}}"},
{"name": "lifecycle_stage", "value": "customer"},
{"name": "onboarding_status", "value": "pending"}
]
}
},
"name": "Update HubSpot",
"type": "n8n-nodes-base.hubspot",
"position": [650, 200]
},
{
"parameters": {
"resource": "card",
"operation": "create",
"idList": "YOUR_TRELLO_LIST_ID",
"name": "Onboard: {{$node['Extract Customer Data'].json.customer_name}}",
"description": "**Customer:** {{$node['Extract Customer Data'].json.customer_email}}\n**Plan:** {{$node['Extract Customer Data'].json.plan_type}}\n**Stripe ID:** {{$node['Extract Customer Data'].json.customer_id}}\n\n**Onboarding Checklist:**\n- [ ] Send welcome email\n- [ ] Schedule kickoff call\n- [ ] Share documentation\n- [ ] Set up account access\n- [ ] Complete 7-day check-in"
},
"name": "Create Trello Card",
"type": "n8n-nodes-base.trello",
"position": [650, 300]
},
{
"parameters": {
"channel": "#new-customers",
"text": "🎉 *New Customer Alert*\n\n*Name:* {{$node['Extract Customer Data'].json.customer_name}}\n*Email:* {{$node['Extract Customer Data'].json.customer_email}}\n*Plan:* {{$node['Extract Customer Data'].json.plan_type}}\n\nTrello card created. Let's make them successful!"
},
"name": "Slack Notification",
"type": "n8n-nodes-base.slack",
"position": [650, 400]
},
{
"parameters": {
"resource": "listMember",
"operation": "create",
"list": "={{$node['Extract Customer Data'].json.plan_type === 'pro' ? 'PRO_LIST_ID' : 'STARTER_LIST_ID'}}",
"email": "={{$node['Extract Customer Data'].json.customer_email}}",
"options": {
"status": "subscribed",
"mergeFields": {
"FNAME": "={{$node['Extract Customer Data'].json.customer_name.split(' ')[0]}}",
"PLAN": "={{$node['Extract Customer Data'].json.plan_type}}"
},
"tags": ["new_customer", "={{$node['Extract Customer Data'].json.plan_type}}"]
}
},
"name": "Add to Mailchimp",
"type": "n8n-nodes-base.mailchimp",
"position": [650, 500]
}
],
"connections": {
"Stripe Trigger": {"main": [[{"node": "Extract Customer Data"}]]},
"Extract Customer Data": {"main": [[{"node": "Update HubSpot"}, {"node": "Create Trello Card"}, {"node": "Slack Notification"}, {"node": "Add to Mailchimp"}]]}
}
}
Setup:
Import JSON into n8n
Connect Stripe webhook (add your webhook secret)
Add HubSpot API credentials
Connect Trello and add your target list ID
Connect Slack and set your notification channel
Connect Mailchimp and update list IDs for each plan tier
Expansion Ideas:
Add plan-specific onboarding sequences (different Trello templates per tier)
Connect to Calendly to auto-schedule kickoff calls
Add a 7-day delayed check-in automation
Build a "customer health" score based on onboarding completion
Trigger different Mailchimp sequences based on plan tier
Why This Works:
Manual onboarding creates delays and inconsistency. This workflow ensures every new customer gets the same systematic treatment within seconds of payment. Your ops team gets visibility, your CRM stays accurate, and your marketing lists stay segmented—without anyone lifting a finger.
THE BOTTOM LINE
OpenAI's $10 billion Cerebras deal isn't about chips—it's about the new competitive logic of AI. The winners aren't the companies with the biggest models. They're the ones building diversified compute portfolios that match the right silicon to the right workload. Inference speed is the new battleground, and real-time AI is the prize.
That same logic applies at every layer of the stack. Edge processing will handle 75% of enterprise data by next year because latency kills. Your API integrations should be cross-sell triggers, not passive pipes—hit users at moments of success, not cold inboxes. And the tools breaking out aren't chatbots that generate text; they're agents that execute work while you focus on decisions.
The playbook is consistent: optimise for speed, match infrastructure to task, and automate the mechanical so humans can focus on judgment.
If you're building, build for real-time. If you're investing, follow the compute. If you're operating, turn every integration into a revenue channel.
Ship daily.
HackrLife Daily is read by growth marketers at Google, Adobe, LinkedIn, and creators building the future.