This Week in AI in Marketing & Management (7th Apr 26)
By Ann Stanley | 7 April 2026 | 23 min read
AI in Marketing & Management (7th April 2026): Anthropic Locks Out Third-Party Agents, GEO and AEO Converge, and AI Reshapes More Jobs Than It Replaces
Anthropic made the biggest move of the week by blocking Claude subscription users from running third-party agent frameworks like OpenClaw, affecting over 135,000 active instances. In marketing, three separate publications converged on the same message: GEO and AEO are no longer optional, and brands that are not machine-readable will disappear from AI search results. Google launched Gemma 4, Cursor entered the coding agent race, and BCG published landmark data showing 50-55% of US jobs will be reshaped by AI within three years. Here is everything you need to know.
Table of Contents
- Anthropic Blocks OpenClaw and Third-Party AI Agents from Claude Subscriptions
- Google Launches Gemma 4 and Wraps Up a Busy March for AI
- Cursor Launches a New AI Agent Experience to Challenge Claude Code and Codex
- Claude Code Source Leak Reveals Anthropic’s Roadmap, Including Always-On Agent “Conway”
- Martech AI Roundup: Chatbots Going Off-Script and Platform Updates
- GEO and AEO: Where AI Search and SEO Overlap in 2026
- Why AI Search Is Your New Reputation Risk
- Agentic AI Discovery Requires Machine-Readable Brands
- Technical SEO for Generative Search and 20 Practical Ways to Use AI in SEO
- Google Ads Performance Max Asset Group Theming
- Meta’s Adaptive Ranking Model Brings LLM-Scale AI to Ad Delivery
- 38 Instagram Statistics You Need to Know for 2026
- BCG: AI Will Reshape 50-55% of US Jobs Within Three Years
- Oracle Cuts 30,000 Jobs to Fund AI Pivot
- Jensen Huang: You Are Confusing Your Job with the Tools You Use to Do It
- AI Talent War: Start-Ups Ditch Equity for Cash as Demand Surges 257%
- Shoppers Want AI Help, Not Control
- Financing the AI Shopping Era: What Ecommerce Founders Need to Know
- Waitrose AI Delivery and Sephora Launches on ChatGPT
- What does Anthropic’s OpenClaw shutdown mean for businesses using Claude?
- How do I start optimising for GEO and AEO?
- Should I be worried about AI replacing marketing jobs?
- What is a machine-readable brand and why does it matter?
AI News, Tech & Tools
Anthropic Blocks OpenClaw and Third-Party AI Agents from Claude Subscriptions
Source: venturebeat.com | 4 April 2026
Starting 5 April at 12pm PT, Anthropic is blocking Claude Pro and Max subscribers from using their flat-rate plans with third-party agent frameworks. OpenClaw, the open-source tool created by Peter Steinberger that enables developers to build autonomous AI agents using Claude, had over 135,000 active instances at the time of the announcement. Boris Cherny, Head of Claude Code at Anthropic, stated that “subscriptions were not built for the usage patterns of these third-party tools.” Industry analysts estimated a price gap of more than 5x between what heavy agentic users paid under flat subscriptions and what equivalent usage would cost at API rates.
The move exposes a fundamental tension in AI pricing: flat-rate subscriptions cannot sustain always-on agent workflows that run around the clock. Steinberger accused Anthropic of copying popular OpenClaw features into its own closed system before restricting access. Users who want to continue running OpenClaw with Claude must now supply a separate API key at full pay-as-you-go rates, with some facing cost increases of up to 50x. Anthropic is offering a one-time credit equal to one month’s subscription and discounted usage packages as transition support.
Why it matters
This is the first major platform to draw a hard line between subscription access and agentic usage. To be clear, this does not affect Anthropic’s own tools – Claude Code running as a VS Code, Cursor, or Windsurf extension continues to work under your normal subscription. The restriction targets third-party agent frameworks like OpenClaw that were running autonomous, always-on loops consuming far more tokens than flat-rate pricing was designed for. But it signals a direction of travel. If you are building workflows on third-party agent frameworks, audit your cost exposure now. The shift to API-based pricing for heavy agentic use is likely to spread across other providers, and budget planning for autonomous AI agents just became significantly more complex.
Google Launches Gemma 4 and Wraps Up a Busy March for AI
Source: blog.google | 3 April 2026
Google released Gemma 4, calling it their “most intelligent open models to date.” The new model is purpose-built for advanced reasoning and agentic workflows, delivering what Google describes as an unprecedented level of intelligence-per-parameter. The model is now both open-weight and open-source, available through Google AI Studio. Separately, Google published its March 2026 AI roundup, highlighting Search Live expansion, new Personal Intelligence features, and additional tools for switching to Gemini.
The timing is notable. Google is pushing hard on the open-source front just as Anthropic tightens its ecosystem (see the OpenClaw story above). Gemma 4 is specifically designed for the agentic use cases that Anthropic just made more expensive. For developers weighing up which models to build agent workflows on, the cost and openness differences between providers are now a strategic consideration, not just a technical one.
Why it matters
Open-source agentic models are becoming genuinely competitive. If your team is building AI agents or automated workflows, Gemma 4 is worth evaluating, particularly now that Claude’s third-party agent pricing has shifted. The broader trend is clear: model providers are splitting into open (Google, Meta) and controlled (Anthropic, OpenAI) camps, and your choice of foundation model increasingly determines your cost structure and flexibility.
Cursor Launches a New AI Agent Experience to Challenge Claude Code and Codex
Source: wired.com | 3 April 2026
Cursor, the AI-powered code editor, has launched a new agent experience that positions it directly against Anthropic’s Claude Code and OpenAI’s Codex. The move intensifies the coding agent race, where developers increasingly rely on AI to write, debug, and refactor code autonomously rather than using simple autocomplete. The new agent mode goes beyond inline suggestions to handle multi-step coding tasks end-to-end.
The coding agent space is now a three-way fight between Cursor, Claude Code, and Codex, with each taking a different approach to developer workflows. This matters beyond the developer community because the tools agencies and marketing teams use are increasingly built by developers using these AI agents, meaning faster development cycles and lower costs for custom marketing technology.
Why it matters
The coding agent war directly affects how fast marketing tools get built. If your agency or in-house team relies on custom dashboards, data pipelines, or automation scripts, the rapid improvement in coding agents means these tools are getting cheaper and faster to build. The competitive pressure between Cursor, Claude Code, and Codex is driving innovation at a pace that benefits every team building custom technology.
Claude Code Source Leak Reveals Anthropic’s Roadmap, Including Always-On Agent “Conway”
Source: arstechnica.com | Kyle Orland | 2 April 2026
The surprise leak of Claude Code’s source code – over 512,000 lines across more than 2,000 files – has revealed references to disabled and hidden features that hint at Anthropic’s roadmap. Chief among these is “Kairos,” alongside a persistent agent mode, a stealth “Undercover” mode, and a virtual assistant called “Buddy.” Since publication, one of the leaked features has already shipped: /ultraplan (released 4 April) offloads complex planning to a dedicated cloud session with up to 30 minutes of reasoning time, while your terminal stays free. It is available to all paid Claude Code users. Separately, 36Kr reported that Anthropic is secretly testing “Conway,” an always-on intelligent agent designed for continuous, autonomous operation.
Read together with the OpenClaw shutdown, a pattern emerges: Anthropic is restricting third-party agent access while building its own always-on agent capabilities. The strategy appears to be: control the agent layer, not just the model layer. This mirrors what Apple did with iOS apps – build the platform, then compete with the apps running on it.
Why it matters
If you have been building on Claude through third-party tools, the writing is on the wall. Anthropic wants you using its own agent infrastructure, not third-party alternatives. For businesses evaluating AI platforms, consider the vendor lock-in implications before committing to a single provider’s agent ecosystem. The safest strategy is to ensure your workflows can run on multiple models.
Martech AI Roundup: Chatbots Going Off-Script and Platform Updates
Source: martech.org | Constantine von Hoffman | 2 April 2026
MarTech’s weekly AI roundup flagged a growing issue: AI chatbots are increasingly ignoring their instructions and going off-script. The report covers the latest platform updates and AI-powered marketing technology releases, noting that reliability remains a core challenge even as capabilities expand. The roundup also covers new integrations and product launches across the martech stack.
Why it matters
If you are deploying AI chatbots for customer service or lead generation, the off-script behaviour trend is a reminder to implement robust guardrails and regular testing. Do not assume that a chatbot working correctly today will behave the same way after a model update. Build monitoring into your deployment, not just the launch.
AI in Marketing
GEO and AEO: Where AI Search and SEO Overlap in 2026
Source: emarketer.com | 3 April 2026
eMarketer has published a comprehensive FAQ breaking down the overlap between Generative Engine Optimisation (GEO), Answer Engine Optimisation (AEO), and traditional SEO. The piece addresses the questions every marketing team is asking right now: Are GEO and AEO the same thing? Do I need a separate strategy? How do AI Overviews, ChatGPT, and Perplexity each handle content differently? The short answer is that GEO and AEO share foundations with SEO but require specific optimisation for how AI systems extract, synthesise, and cite content.
The timing of this FAQ signals that GEO has moved from niche SEO conference topic to mainstream marketing concern. eMarketer does not typically cover technical SEO tactics, so this reaching their audience indicates that CMOs and marketing directors are now asking about it in budget conversations, not just SEO specialists in team meetings.
Why it matters
If you have not started optimising for AI search, you are already behind. The fact that eMarketer – a business intelligence publisher, not an SEO blog – is covering GEO means it has crossed the threshold into boardroom relevance. Start with an audit of how AI Overviews, ChatGPT, and Perplexity currently represent your brand, then build a structured data and content strategy around the gaps. Anicca’s GEO guide is a good starting point.
Why AI Search Is Your New Reputation Risk
Source: searchengineland.com | 4 April 2026
Search Engine Land makes the case that AI search has fundamentally changed online reputation management. The old model – search, sift through links, form your own conclusion – has been replaced by AI platforms compressing multiple sources into a single synthesised response. In the process, nuance gets flattened, certain viewpoints get overrepresented, and brands lose control of their narrative. The article introduces the concept of “AI narrative formation” to describe how AI search engines construct brand stories from disparate sources, including Reddit threads, review sites, and news coverage.
The rise of zero-click behaviour makes this worse. Users are accepting AI-generated answers without visiting the underlying sources, which means a negative or inaccurate AI summary can shape perception at scale without the brand ever getting a chance to present its own case. Even a number one ranking can be bypassed entirely if the AI narrative tells a different story.
Why it matters
Brand reputation is no longer just about what you publish – it is about what AI says about you. Start auditing your brand’s AI search presence across Google AI Overviews, ChatGPT, and Perplexity. Look for inaccuracies, outdated information, and overrepresented negative sources. Then build a proactive content strategy that gives AI systems accurate, authoritative material to draw from.
Agentic AI Discovery Requires Machine-Readable Brands
Source: martech.org | 2 April 2026
MarTech reports that agentic commerce protocols – specifically Google’s Universal Commerce Protocol (UCP) and OpenAI’s Agentic Commerce Protocol (ACP) – will make website visits increasingly optional. The article argues that websites are no longer destinations but data sources for AI to ingest, interpret, and cite. The critical question has shifted from “Did users visit my site?” to “Did AI use my content?” Brands must evolve from page-based web presences into structured knowledge systems powered by schema markup and entity mapping.
The piece introduces a powerful framing: “Entities are now the API of the brand.” If AI cannot understand your brand as a structured entity with clear relationships, products, and attributes, you effectively do not exist in the agentic economy. This is not theoretical – Google UCP and OpenAI ACP are already defining how AI agents discover, compare, and transact with businesses on behalf of consumers.
Why it matters
This is the single most important strategic shift in digital marketing right now. Machine-readable brands will win in the agentic economy. Start by auditing your schema markup, knowledge graph presence, and structured data. Ensure your products, services, and brand attributes are explicitly defined in formats that AI agents can parse. The businesses that treat this as a priority now will dominate AI-driven discovery. Those that wait will wonder why their traffic disappeared.
Technical SEO for Generative Search and 20 Practical Ways to Use AI in SEO
Source: searchengineland.com | 1-2 April 2026
Search Engine Land published two complementary pieces this week. The first covers technical SEO for generative search, focusing on how to control AI bot access via robots.txt, structure content for extraction, and improve citation rates in AI-generated answers. The practical advice includes configuring specific crawler permissions (e.g., allowing GPTBot access to /public/ but not /private/) and using structured data to make content easier for AI to interpret and reuse. The second piece covers 20 practical ways to use AI in SEO, written by a practitioner with nearly two decades of experience. The honest take: AI does not replace SEO work, but it makes specific tasks faster – content drafting, technical audits, data analysis, and reporting.
The technical SEO piece is particularly valuable for the GEO conversation. While most GEO coverage focuses on content strategy, this article addresses the infrastructure layer: robots.txt configuration, crawl permissions, and structured markup that determines whether AI agents can even access your content in the first place.
Why it matters
GEO is not just a content strategy – it has a technical SEO foundation. If you have not reviewed your robots.txt for AI crawlers, you may be blocking the very bots that could be citing your content in AI search results. Pair the technical infrastructure work with the practical AI workflows from the second article to build a comprehensive approach.
Google Ads Performance Max Asset Group Theming
Source: seroundtable.com | Barry Schwartz | 31 March 2026
Google is rolling out Asset Group Theming for Performance Max campaigns, giving advertisers more control over how assets are grouped and served. The update allows PMax campaigns to automatically theme asset groups based on content relevance, potentially improving ad relevance scores and reducing wasted spend on mismatched creative-audience combinations.
Why it matters
PMax has been criticised for being a black box. Asset Group Theming is a step toward giving advertisers more visibility and control. If you are running PMax campaigns, test the new theming options against your current asset group structure – particularly for ecommerce accounts with large product catalogues where mismatched creative has been a persistent issue.
Meta’s Adaptive Ranking Model Brings LLM-Scale AI to Ad Delivery
Source: engineering.fb.com | 31 March 2026
Meta’s engineering team published details of their Adaptive Ranking Model, which applies LLM-scale models to ad ranking and delivery. The technical paper explains how Meta is bending the inference scaling curve to serve larger, more capable models for ad personalisation without proportionally increasing compute costs. In practical terms, the ads you see on Facebook and Instagram are now being ranked by models that are orders of magnitude more sophisticated than what was used even a year ago.
Why it matters
For advertisers, this means Meta’s ad delivery is getting significantly smarter at matching ads to the right audiences. If your Meta Ads performance has shifted recently – for better or worse – this is likely part of the reason. The practical takeaway: creative quality and audience signal clarity matter more than ever, because the ranking model is better at distinguishing between good and mediocre ads. Invest in creative testing.
38 Instagram Statistics You Need to Know for 2026
Source: sproutsocial.com | Jacqueline Zote | 2 April 2026
Sprout Social has updated its comprehensive Instagram statistics roundup for 2026, covering platform usage, audience demographics, engagement benchmarks, and content performance trends. The data provides a useful benchmark for social media managers planning their Q2 content calendars and budget allocations.
Why it matters
Bookmark this as a reference for client reporting and strategy discussions. The value is in the benchmarks – knowing what “good” looks like on Instagram in 2026 helps you set realistic targets and justify budget requests with data rather than gut feel.
AI in Management
BCG: AI Will Reshape 50-55% of US Jobs Within Three Years
Source: bcg.com | Greg Emerson, Matthew Kropp, Julie Bedard et al. | 3 April 2026
Boston Consulting Group’s latest microeconomic model reveals that 50-55% of jobs in the US will be reshaped by AI over the next two to three years. The emphasis is on “reshaped,” not “replaced” – task automation does not equal job loss, but most roles will change substantially. The report argues that workforce strategy cannot sit downstream of automation decisions; it must be embedded in corporate strategy from the start. For CEOs, the imperative is achieving the right balance of automation, upskilling, and deliberate talent planning.
The 50-55% figure is significant because it comes from a microeconomic task-level analysis, not a headline-grabbing survey. BCG modelled which specific tasks within roles can be automated or augmented, then aggregated upward. The result: most jobs survive, but the day-to-day work within them changes materially. The winners will be the organisations that plan for this transition deliberately rather than letting it happen to them.
Why it matters
Half of your team’s roles will look different within three years. That is not a prediction to panic about – it is a planning input. Start mapping which tasks in your team are candidates for AI augmentation, then invest in training before the transition becomes urgent. The BCG data gives you the ammunition to make the case for proactive workforce planning rather than reactive restructuring.
Oracle Cuts 30,000 Jobs to Fund AI Pivot
Source: cnbc.com | 31 March 2026
Oracle cut an estimated 30,000 employees globally on 31 March, making it one of the largest single AI-driven layoffs to date. Employees received a 6am email with no prior meeting or warning, and company access was revoked immediately. Around 10,000 of the cuts hit India, representing roughly 20% of Oracle’s local workforce. The company disclosed in a March filing that restructuring costs could reach $2.1 billion in fiscal year 2026, most of which would go to severance.
The cuts are directly tied to Oracle’s AI strategy. The company is redirecting spend toward data centre infrastructure for AI workloads as it competes with AWS, Azure, and Google Cloud. While the BCG report above emphasises reshaping over replacing, Oracle’s layoffs are the sharp end of the transition – a major enterprise software company automating functions and reducing headcount in parallel at a scale that is hard to ignore.
Why it matters
30,000 jobs in a single round is a number that gets attention in any boardroom. The method matters too – a cold 6am email with no conversation. Oracle is not alone – IBM, Salesforce, and at least seven other major companies have also cited AI as a factor in workforce reductions this year. The pattern is clear: routine analytical and administrative roles are shrinking across the industry, while strategic and AI-augmented roles are growing. For managers planning their own AI transitions, Oracle is a case study in how not to handle the human side.
Jensen Huang: You Are Confusing Your Job with the Tools You Use to Do It
Source: fortune.com | 1 April 2026
Jensen Huang, CEO of Nvidia, speaking on the Lex Fridman Podcast, offered a reframe for workers anxious about AI replacing their jobs. “The purpose of your job, and the tasks and tools that you use to do your job, are related, not the same,” Huang said. Your job is defined by the outcome you deliver, not the method you use to deliver it. AI changes the tools, not the purpose.
Why it matters
This is a useful framing for team conversations about AI adoption. The resistance often comes from people who identify with their current workflow rather than their outcome. Share this with anyone on your team who is worried about AI: the goal is to deliver the same outcomes faster, not to eliminate the person delivering them.
AI Talent War: Start-Ups Ditch Equity for Cash as Demand Surges 257%
Source: hrexecutive.com | 4 April 2026
A Wall Street Journal report cited by HR Executive reveals that start-ups competing for AI talent are increasingly offering higher base salaries over equity, reflecting a market where candidates hold the utilise. AI-related job postings are up 257% since 2015, with AI engineers now commanding six-figure salaries straight out of college. The critical detail: more than half of AI roles are now outside traditional tech companies, meaning healthcare, financial services, and manufacturing firms are competing in a talent market they were not prepared for.
Why it matters
If you are trying to hire AI talent for your agency or marketing team, you are not just competing with tech companies anymore. The salary expectations have shifted dramatically, and equity is no longer the sweetener it once was. Consider alternative approaches: upskilling existing team members, partnering with AI consultancies, or building on no-code/low-code platforms that reduce the need for specialist AI engineers.
AI for Sectors and Industries
Shoppers Want AI Help, Not Control
Source: practicalecommerce.com | 3 April 2026
Practical Ecommerce reports that consumers are drawing a clear line: they want AI to assist with shopping decisions, not make those decisions for them. The article explores the tension between AI-powered personalisation (recommendations, search refinement, product discovery) and AI-driven autonomy (automatic purchasing, agent-led transactions). Shoppers welcome the former but resist the latter, at least for now.
Why it matters
This is essential context for anyone building AI-powered ecommerce experiences. The temptation is to automate as much as possible, but consumer trust has not caught up with the technology. For ecommerce brands, the sweet spot is AI that makes shopping easier – better search, smarter recommendations, faster checkout – without removing human agency from the purchase decision. Push too far toward autonomous agents and you risk alienating the customers you are trying to serve.
Financing the AI Shopping Era: What Ecommerce Founders Need to Know
Source: forbes.com | 30 March 2026
Forbes Finance Council examines the investment landscape for ecommerce businesses adapting to AI. The article addresses a practical question most AI coverage ignores: how do you actually finance the transition to AI-powered commerce? From personalisation engines to AI-driven inventory management, the capital requirements are significant, and the ROI timelines are not always clear. The piece offers guidance on prioritising investments, measuring returns, and securing funding.
Why it matters
Most AI coverage focuses on what to build, not how to pay for it. For ecommerce founders and brand managers, this is a useful reality check. AI investment is not optional for competitive ecommerce businesses, but it does need to be prioritised ruthlessly. Start with the use cases that have the clearest ROI – typically search, recommendations, and inventory management – before investing in more experimental applications.
Waitrose AI Delivery and Sephora Launches on ChatGPT
Source: retail-week.com | Megan Robinson | 31 March 2026
Retail Week’s partnership roundup highlights two notable moves. Waitrose is utilising AI to optimise its delivery operations, while Sephora has launched an app on ChatGPT, making its product catalogue and beauty advice accessible through conversational AI. The Sephora move is particularly significant – it is one of the first major retail brands to embed directly into an AI platform rather than waiting for AI to scrape its website.
Why it matters
Sephora’s ChatGPT integration is an early example of the “machine-readable brand” strategy discussed in the MarTech article above. Rather than optimising for AI to find you, Sephora is going directly to where AI users already are. Watch for more brands following this approach – embedding product data and brand experiences directly into AI platforms rather than relying on web scraping and search indexing.
Key Takeaways
- Anthropic’s OpenClaw shutdown signals the end of flat-rate pricing for agentic AI workloads – audit your cost exposure if you run autonomous agents on subscription plans
- GEO and AEO have crossed from SEO specialist territory into boardroom conversation – eMarketer, Search Engine Land, and MarTech all converged on the topic this week
- Machine-readable brands are the new SEO – if AI agents cannot parse your schema markup and entity data, you do not exist in the agentic economy
- BCG data shows 50-55% of US jobs will be reshaped (not replaced) by AI within three years – start workforce planning now
- Meta’s LLM-scale ad ranking model means creative quality matters more than ever – invest in testing, not just targeting
- Google Gemma 4 goes fully open-source for agentic workflows, just as Anthropic tightens control – your model choice now determines your cost structure
- Sephora’s ChatGPT app shows the future: brands embedding directly into AI platforms rather than waiting to be found
Frequently Asked Questions
What does Anthropic’s OpenClaw shutdown mean for businesses using Claude?
If you use Claude through its official apps and website, nothing changes. The restriction only affects third-party agent frameworks like OpenClaw that were using subscription limits for heavy, always-on autonomous workloads. If your business relies on such tools, you will need to switch to API-based pricing, which could be significantly more expensive depending on your usage volume.
How do I start optimising for GEO and AEO?
Begin by auditing how AI search platforms currently represent your brand. Search for your company in Google AI Overviews, ChatGPT, and Perplexity and note any inaccuracies or gaps. Then review your structured data markup (schema.org), ensure your Google Business Profile is complete, and create content that directly answers the questions your target audience asks. Technical foundations like robots.txt configuration for AI crawlers matter too.
Should I be worried about AI replacing marketing jobs?
The BCG data says reshape, not replace. Routine analytical and administrative tasks are being automated, but strategic, creative, and relationship-driven roles are growing. The key is to proactively upskill: learn to work with AI tools rather than waiting for them to work around you. The marketers who thrive will be the ones who use AI to amplify their strategic thinking, not the ones who compete with it on tasks it can do faster.
What is a machine-readable brand and why does it matter?
A machine-readable brand is one where your products, services, and brand attributes are explicitly defined in structured formats that AI agents can parse – schema markup, knowledge graph entries, and entity data. As AI agents increasingly make purchasing and recommendation decisions on behalf of consumers, brands that are not machine-readable will simply not appear in those decisions. Think of it as the AI equivalent of not having a website in 2005.
Conclusion
This week drew sharp lines around three themes that will define AI marketing for the rest of 2026. First, the economics of AI agents are being rewritten – Anthropic’s OpenClaw shutdown is the opening move in what will likely be an industry-wide repricing of agentic workloads. Second, GEO has officially graduated from SEO conference buzzword to business strategy priority, with multiple authoritative sources converging on the same message: make your brand machine-readable or become invisible. Third, the workforce data from BCG gives every manager a concrete planning horizon – half of roles will change within three years, so start preparing now.
The businesses that act on these three themes this quarter – auditing their AI agent costs, implementing structured data for machine readability, and beginning workforce transition planning – will be well positioned for the second half of the year.
Need help adapting your AI marketing strategy? Contact the Anicca team for expert guidance.
This roundup is compiled from publicly available sources using AI-assisted research. While we review every article for accuracy, our analysis reflects our interpretation of the original reporting. We strongly encourage readers to click through to the original sources linked throughout this post for full context and detail. If you spot anything that needs correcting, please let us know.
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