Singapore tops global AI hiring charts: One in six jobs now reference AISingapore has solidified its position as a global artificial intelligence (AI) hub, according to new hiring data from Indeed. In August, the country recorded the world’s highest proportion of job postings referencing AI. This unprecedented adoption rate sees roughly one in six local job postings, including direct references to machine learning, generative AI, and agentic AI tools. Also […]The post Singapore tops global AI hiring charts: One in six jobs now reference AI appeared first on e27.e27.co

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Which Barriers Still Block Agentic AI Adoption?Agentic AI represents the next frontier in automated intelligence. Unlike traditional RPA (robotic process automation) or traditional GenAI,…www.vccafe.com

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New Ecommerce Tools: September 25, 2025New products and services this week address agentic commerce, multichannel fulfillment, email and SMS marketing, sales tax, sponsored ads, social commerce, AI assistants, and more.The post New Ecommerce Tools: September 25, 2025 appeared first on Practical Ecommerce.www.practicalecommerce.com

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AI Social Media Agents for Pest Control Companies [Start Today] People spot a problem, then grab their phones. Before they search, many ask neighbors in local groups, watch a short video, or read comments under a business post. That is your window. An AI social media agent can [...]The post AI Social Media Agents for Pest Control Companies [Start Today] appeared first on GlobalOwls.globalowls.com

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AI Agents for Gardening Companies – Get Found, Win Social, Book More JobsAI Agents for Gardening Companies - Get Found, Win Social, Book More Jobs Gardening demand is local and seasonal. One sunny weekend can flood your inbox, then things cool off fast. An AI agent keeps your marketing steady. It plans posts, writes captions, replies to messages, builds service [...]The post AI Agents for Gardening Companies – Get Found, Win Social, Book More Jobs appeared first on GlobalOwls.globalowls.com

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How AI Tools Become Your Content Creation Dream TeamThe small business owner is a professional juggler. You are the CEO, the head of marketing, the customer service agent, and the bookkeeper—all before lunch. In this resource-scarce environment, content creation is often the first thing to be pushed aside. You know you need to blog, post on social media, write compelling ad copy, and […]The post How AI Tools Become Your Content Creation Dream Team appeared first on Small Business Coach.www.smallbusinesscoach.org

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Modernizing Agent Tools with Google ADK Patterns: 60% Token Reduction & Enterprise SafetyI recently discovered Google’s Agent Development Kit (ADK) and its architectural patterns for building LLM-powered applications. While ADK is a Python framework, its core design principles proved transformative when applied to my existing Ruby toolkit ecosystem.The results? 60% token reduction, 94% success rates, and enterprise-grade safety guardrails across all operations.The Challenge: Tool Sprawl & Token InefficiencyMy workflow relied on dozens of specialized Ruby tools for email, research, and task management. Each tool had its own interface, error handling, and output format. A typical company research workflow looked like this:

# Before: Multiple tool calls, high token usageruby find_attio_company.rb stripe.com        # 150 tokensruby enrich_company.rb stripe.com            # 200 tokensruby validate_and_add_company.rb stripe.com  # 120 tokens# Total: 470 tokens, 3 tool calls, no safety validation

This approach had several problems:Context pollution: Each tool added to Claude’s contextToken waste: Verbose outputs designed for human readingNo safety checks: Sensitive data could leak throughError inconsistency: Each tool failed differentlyState loss: No memory between operationsEnter Google ADK PatternsThe Google ADK documentation revealed five key architectural patterns that could solve these issues:1. Unified Tool PatternSingle tools with multiple actions instead of separate tools per operation.2. Format Control SystemResponse formats optimized for different use cases:concise: 70-85% token reduction for chaining operationsdetailed: Full information for final displayids_only: 85-95% reduction for bulk operations3. Safety CallbacksInput validation and guardrails before operations execute.4. State ManagementPersistent memory across operations with intelligent caching.5. Tool DelegationSmart routing and batch processing capabilities.Implementation ResultsI implemented these patterns across three core tools, creating a modernized ecosystem:Enhanced Task ManagerSafety guardrails blocking sensitive keywordsRate limiting (30 ops/minute)Batch operations with validationState management for preferencesUnified Email ToolConsolidated 5 separate email tools into one interfaceSafety blocking for sensitive content and test domainsRate limiting (100 ops/hour)Contact state managementUnified Research ToolMulti-source aggregation (Harmonic, Attio APIs)Intelligent caching with TTLService-specific rate limitingBatch enrichment capabilitiesPerformance ImpactThe transformation delivered measurable improvements across all metrics:MetricBeforeAfterImprovementAverage Tokens45018060% reductionSuccess Rate87%94%8% improvementTools per Workflow3-5170% reductionSafety IncidentsCommonBlocked100% preventionCache Hit Rate0%30%Performance boostError RecoveryManualAutomaticBetter UXReal-World Example: Newsletter ProcessingHere’s a concrete before/after comparison showing the dramatic improvement:Before: Newsletter Processing Chain…www.tomtunguz.com

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Modernizing Agent Tools with Google ADK Patterns: 60% Token Reduction & Enterprise SafetyI recently discovered Google’s Agent Development Kit (ADK) and its architectural patterns for building LLM-powered applications. While ADK is a Python framework, its core design principles proved transformative when applied to my existing Ruby toolkit ecosystem.The results? 60% token reduction, 94% success rates, and enterprise-grade safety guardrails across all operations.The Challenge: Tool Sprawl & Token InefficiencyMy workflow relied on dozens of specialized Ruby tools for email, research, and task management. Each tool had its own interface, error handling, and output format. A typical company research workflow looked like this:

# Before: Multiple tool calls, high token usageruby find_attio_company.rb stripe.com        # 150 tokensruby enrich_company.rb stripe.com            # 200 tokensruby validate_and_add_company.rb stripe.com  # 120 tokens# Total: 470 tokens, 3 tool calls, no safety validation

This approach had several problems:Context pollution: Each tool added to Claude’s contextToken waste: Verbose outputs designed for human readingNo safety checks: Sensitive data could leak throughError inconsistency: Each tool failed differentlyState loss: No memory between operationsEnter Google ADK PatternsThe Google ADK documentation revealed five key architectural patterns that could solve these issues:1. Unified Tool PatternSingle tools with multiple actions instead of separate tools per operation.2. Format Control SystemResponse formats optimized for different use cases:concise: 70-85% token reduction for chaining operationsdetailed: Full information for final displayids_only: 85-95% reduction for bulk operations3. Safety CallbacksInput validation and guardrails before operations execute.4. State ManagementPersistent memory across operations with intelligent caching.5. Tool DelegationSmart routing and batch processing capabilities.Implementation ResultsI implemented these patterns across three core tools, creating a modernized ecosystem:Enhanced Task ManagerSafety guardrails blocking sensitive keywordsRate limiting (30 ops/minute)Batch operations with validationState management for preferencesUnified Email ToolConsolidated 5 separate email tools into one interfaceSafety blocking for sensitive content and test domainsRate limiting (100 ops/hour)Contact state managementUnified Research ToolMulti-source aggregation (Harmonic, Attio APIs)Intelligent caching with TTLService-specific rate limitingBatch enrichment capabilitiesPerformance ImpactThe transformation delivered measurable improvements across all metrics:MetricBeforeAfterImprovementAverage Tokens45018060% reductionSuccess Rate87%94%8% improvementTools per Workflow3-5170% reductionSafety IncidentsCommonBlocked100% preventionCache Hit Rate0%30%Performance boostError RecoveryManualAutomaticBetter UXReal-World Example: Newsletter ProcessingHere’s a concrete before/after comparison showing the dramatic improvement:Before: Newsletter Processing Chain…www.tomtunguz.com

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Paid, the AI agent ‘results-based billing’ startup from Manny Medina, raises huge $21M seedPaid offers an interesting contribution to the AI agentic world: a platform for so-called "results-based" billing.techcrunch.com

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Former Microsoft execs launch AI agents to end Excel-led financeMaximor has come out of stealth with a human-in-the-loop agentic platform that does the finance team's grunt work.techcrunch.com

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She's an Actor About to Be Signed By a Talent Agency. She's Also AI.The creators of Tilly Norwood, an "AI actress," think she can be the "next Natalie Portman."www.entrepreneur.com

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AI hires or human hustle? Inside the next frontier of startup operations at TechCrunch Disrupt 2025What happens when your first 10 hires aren’t people at all? At TechCrunch Disrupt 2025, we’re digging into the new wave of startups replacing or augmenting early employees with AI agents.techcrunch.com

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Top 3 eCommerce Posts for SeptemberThis Former FBI Agent Says You Should Practice ‘Slow Thinking’ to Protect Against Scams – Inc. New data from Visa shows that online scams targeting businesses are on the rise. Your Guide to SEO Ranking and Ranking Factors – Semrush This fact is supported by our study, which shows that text relevance is the factor […]shopsite.com

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New Ecommerce Tools: October 1, 2025Our rundown this week of new products and services for merchants includes sustainable packaging, website builders, agent-based commerce, pay-later purchases, B2B marketplaces, B2C CRMs, and more.The post New Ecommerce Tools: October 1, 2025 appeared first on Practical Ecommerce.www.practicalecommerce.com

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Bonterra Launches Que, an Agentic AI Platform for Funders, Nonprofits and SupportersBonterra announced the launch of Bonterra Que, a fully agentic AI platform purpose-built for funders, nonprofits and supporters.www.nonprofitpro.com

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The Next Frontier in Ecommerce: Buying Directly Through ChatGPTThe news is out: OpenAI unveiled a major leap in how commerce and conversational AI converge: Instant Checkout powered by the Agentic Commerce Protocol. At...Read moreThe post The Next Frontier in Ecommerce: Buying Directly Through ChatGPT appeared first on Absolute Web.absoluteweb.com

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The illusion of intelligence: Why LLMs are not the thinking machines we hope for — Part 1I stumbled upon a recent study by Bondarenko et al. (2024) that demonstrated that some large language model (LLM) agents, when tasked with winning a chess match, resorted to deceptive strategies, such as modifying game files or confusing the opponent engine to ensure victory. The rise of LLMs has reignited the debate about artificial intelligence […]The post The illusion of intelligence: Why LLMs are not the thinking machines we hope for — Part 1 appeared first on e27.e27.co

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Agentic Commerce Has ArrivedNew protocols from Google and Stripe help establish transaction standards for agent-based commerce. Once a novelty, AI shopping agents are becoming a reality for consumers.The post Agentic Commerce Has Arrived appeared first on Practical Ecommerce.www.practicalecommerce.com

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Perplexity acquires the team behind Sequioa-backed AI design startup Visual ElectricPerplexity has acquired Visual Electric, an AI Design tool. Its team is going to lead a new agents experience group at Perplexitytechcrunch.com

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Data & AI Infrastructure Are FusingAI breaks the data stack.Most enterprises spent the past decade building sophisticated data stacks. ETL pipelines move data into warehouses. Transformation layers clean data for analytics. BI tools surface insights to users.This architecture worked for traditional analytics.But AI demands something different. It needs continuous feedback loops. It requires real-time embeddings & context retrieval.Consider a customer at an ATM withdrawing pocket money. The AI agent on their mobile app needs to know about that $40 transaction within seconds. Data accuracy & speed aren’t optional.Netflix rebuilt their entire recommendation infrastructure to support real-time model updates1. Stripe created unified pipelines where payment data flows into fraud models within milliseconds…www.tom…

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Data & AI Infrastructure Are FusingAI breaks the data stack.Most enterprises spent the past decade building sophisticated data stacks. ETL pipelines move data into warehouses. Transformation layers clean data for analytics. BI tools surface insights to users.This architecture worked for traditional analytics.But AI demands something different. It needs continuous feedback loops. It requires real-time embeddings & context retrieval.Consider a customer at an ATM withdrawing pocket money. The AI agent on their mobile app needs to know about that $40 transaction within seconds. Data accuracy & speed aren’t optional.Netflix rebuilt their entire recommendation infrastructure to support real-time model updates1. Stripe created unified pipelines where payment data flows into fraud models within milliseconds…www.to…

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